DESC:TECHNICAL FIELD
The present disclosure relates generally to an exercising system. More particularly, the present disclosure relates to a system and a method for gait training.
BACKGROUND
Human beings are required to do exercise to exhibit a fit lifestyle. Accordingly, the majority of people are engaged in various physical activities such as playing, yoga, sports, and gym. Exercises or other physical activities have become a part of lifestyle these days that are required to enhance or maintain physical fitness and overall health and wellness.
People also get prone to mobility issues, which are mainly because of stroke, spinal cord injuries, Parkinson disease, or due to any other neurological disorder. Accordingly, people engage themselves in various exercises to get cured of such diseases. Sometimes, it is difficult or impossible for them to attain mobility of the limbs. Therefore, they require an assistance with walking. There are various systems and devices that helps to attain mobility of the limbs. Conventional systems and devices are not able to properly assist the users in walking.
The existing conventional systems utilizes electric drives that often suffer from reliability issues and high maintenance costs. These systems may not adequately support individuals with specific mobility needs that maybe generated due to conditions like stroke, spinal cord injuries, Parkinson's disease, and other neurological disorders. Moreover, the conventional systems may not effectively address the diverse range of therapeutic requirements these patients require.
In contrast, the pneumatic-driven gait orthosis offer several distinct advantages. They provide passive cushioning, enhancing comfort and adaptability during use. This feature not only supports a more natural walking motion but also contributes to structural integrity, making the system more robust and less prone to mechanical failures. Additionally, pneumatic systems tend to be more cost-effective compared to their electric counterparts, reducing financial burdens for users and healthcare providers alike.
Considering these critical factors, the new design for walk assistance represents a significant advancement over traditional gait training devices. Therefore, there exists a need for an efficient walk assistance system that is capable of solving aforementioned problems of the conventional exercising systems.
SUMMARY
A system is disclosed. The system includes a pair of braces, a first set of sensors, a pneumatic assembly, a second set of sensors, an input unit, and processing circuitry. The pair of braces that are adapted to be worn on legs of a user. The first set of sensors are coupled to the pair of braces and configured to sense one or more metrices that are associated with kinematics of the pair of braces. The pneumatic assembly is coupled to the pair of braces and configured to actuate the pair of braces to move the legs of the user. The second set of sensors are coupled to the pneumatic assembly and configured to sense one or more variables that are associated with the pneumatic assembly. The input unit is configured to (i) receive one or more physiological parameters of the user, and (ii) one or more gait parameters associated with the user. The processing circuitry is configured to the first set of sensors, the second set of sensors, and the input unit and configured to: (i) generate a gait pattern based on the one or more physiological parameters and the one or more gait parameters by way of an AI/ML technique or one or more computational techniques, and (ii) allow the pneumatic assembly to actuate the pair of braces based on the gait pattern, the one or more metrices and the one or more variables in any one of a passive mode, an assistive mode, or an active mode such that (i) in the passive mode, the pair of braces are actuated to move the legs of the user without any effort from the user, (ii) in the assistive mode, the pair of braces are actuated to move the legs with supplemental assistance based on the efforts of the user, and (iii) in the active mode, the pair of braces are actuated to provide adjustable resistance to the legs during movement of the legs.
In some aspects of the present disclosure, the processing circuitry is further configured to update the gait pattern in real time based on one or more changes in the one or more physiological parameters or the one or more gait parameters and/or combination thereof.
In some aspects of the present disclosure, (i) speed of walking, (ii) step length, (iii) ground clearance, (iv) range of motion or (v) acceleration of limbs.
In some aspects of the present disclosure, the one or more physiological parameters includes any one of, or a combination of, a body weight, a height of the user, a length of a leg, muscle strength, range of motion of a joint, body mass index (BMI), balance and coordination, neuromuscular control, posture, previous injuries, joint conditions, neurological conditions, cardiovascular fitness, orthopedic conditions, muscle tone abnormalities, pain levels, circulatory issues, respiratory conditions, or medication effects.
In some aspects of the present disclosure, the one or more metrices includes, one of, a position, speed, or acceleration of the pair of braces.
In some aspects of the present disclosure, the one or more variables includes, one of (i) one or more pressure applied by one or more pistons of the pneumatic assembly, (ii) a flow rate of gas in the pneumatic assembly, or (iii) one or more positions of the one or more pistons in the pneumatic assembly.
In some aspects of the present disclosure, further includes a back support that is coupled to the pair of braces and the pneumatic assembly and adapted to be worn on torso of the user.
In some aspects of the present disclosure, the processing circuitry is further configured to generate an excursion pattern based on the gait pattern by way the AI/ML technique or the one or more computational techniques to allow the pneumatic assembly to actuate the back support to facilitate coordinated movement of the torso of the user in an upward direction and a downward direction with linear movement of knees and hips of the user.
In an aspect of the present disclosure, a method is disclosed. The method includes generating a gait pattern via an AI/ML technique or the one or more computational techniques such that the gait pattern is based on one or more physiological parameters and one or more gait parameters provided to the input unit by way of processing circuitry coupled to a first set of sensors, a second set of sensors, and an input unit. The method further includes allowing a pneumatic assembly coupled to a pair of braces adapted to be worn on legs of a user to actuate the pair of braces to move the legs of the user based on the gait pattern, one or more matrices sensed by the first set of sensors coupled to the pair of braces, and one or more variables sensed by the second set of sensors coupled to the pneumatic assembly in any one of a passive mode, an assistive mode, or an active mode such that (i) in the passive mode, the pair of braces are actuated to move the legs of the user without any effort from the user, (ii) in the assistive mode, the pair of braces are actuated to move the legs with supplemental assistance based on the efforts of the user, and (iii) in the active mode, the pair of braces are actuated to provide adjustable resistance to the legs during movement of the legs by way of the processing circuitry. The method further includes generating an excursion pattern based on the gait pattern via the AI/ML technique or the one or more computational techniques and allow the pneumatic assembly to actuate a back support that is coupled to the pair of braces and the pneumatic assembly and adapted to be worn on torso of the user, to facilitate coordinated movement of the torso of the user in an upward direction and a downward direction with linear movement of knees and hips of the user by way of the processing circuitry.
In some aspects of the present disclosure, the method further includes updating the gait pattern in real-time based on one or more changes in the one or more physiological parameters and the one or more gait parameters), by way of the processing circuitry.
BRIEF DESCRIPTION OF DRAWINGS
FIG. 1A illustrates a front view of a gait training system, in accordance with an aspect of the present disclosure;
FIG. 1B illustrates a block diagram of the gait training system in accordance with an aspect of the present disclosure;
FIG. 1C illustrates a pair of braces of the gait training system of FIG. 1, in accordance with an aspect of the present disclosure;
FIG. 1D illustrates a perspective view of the gait training system of FIG. 1, in accordance with an aspect of the present disclosure;
FIG. 2 illustrates a block diagram of the processing circuitry of the system 100 of FIG. 1, in accordance with an aspect of the present disclosure; and
FIG. 3 illustrates a method 300 of gait training by the system 100 of the FIG. 1, in accordance with an aspect of the present disclosure.
To facilitate understanding, like reference numerals have been used, where possible, to designate like elements common to the figures.
DETAILED DESCRIPTION
Various aspect of the present disclosure provides a system and method for a gait training. The following description provides specific details of certain aspects of the disclosure illustrated in the drawings to provide a thorough understanding of those aspects. It should be recognized, however, that the present disclosure can be reflected in additional aspects and the disclosure may be practiced without some of the details in the following description.
The various aspects including the example aspects are now described more fully with reference to the accompanying drawings, in which the various aspects of the disclosure are shown. The disclosure may, however, be embodied in different forms and should not be construed as limited to the aspects set forth herein. Rather, these aspects are provided so that this disclosure is thorough and complete, and fully conveys the scope of the disclosure to those skilled in the art. In the drawings, the sizes of components may be exaggerated for clarity.
It is understood that when an element is referred to as being “on,” “connected to,” or “coupled to” another element, it can be directly on, connected to, or coupled to the other element or intervening elements that may be present. As used herein, the term “and/or” includes any and all combinations of one or more of the associated listed items.
The subject matter of example aspects, as disclosed herein, is described with specificity to meet statutory requirements. However, the description itself is not intended to limit the scope of this patent. Rather, the inventor/inventors have contemplated that the claimed subject matter might also be embodied in other ways, to include different features or combinations of features similar to the ones described in this document, in conjunction with other technologies.
The aspects herein and the various features and advantageous details thereof are explained more fully with reference to the non-limiting aspects that are illustrated in the accompanying drawings and detailed in the following description. Descriptions of well-known components and processing techniques are omitted so as to not unnecessarily obscure the aspects herein. The examples used herein are intended merely to facilitate an understanding of ways in which the aspects herein may be practiced and to further enable those of skill in the art to practice the aspects herein. Accordingly, the examples should not be construed as limiting the scope of the aspects herein.
FIG. 1A illustrates a front view of a gait training system 100 (hereinafter referred to as and designated as “the system 100”). The system 100 may be adapted to provide gait training to the user. The system 100 may be operated in various modes (i.e., exercise modes). For example, the system 100 may be adapted to provide various exercise patterns that may involve flexion and extension of each joint in which range of motions, speed of exercises and number of repetitions may be controlled individually. The system 100 may be driven by a pneumatic mechanism. The pneumatic mechanism powers robotic legs, enabling users to replicate natural human walking patterns. The system 100 includes AI-based control for real-time feedback and adjustments, ensuring precise gait training.
The system 100 may include a frame 102, a base 104, a first set of sensors 106a-n (hereinafter collectively referred to and designated as “the first set of sensors 106”), a second set of sensors 108a-n (hereinafter collectively referred to and designated as “the second set of sensors 108”), an input unit 110, a user interface 112, processing circuitry 114, a pair of braces 116a and 116b (hereinafter collectively referred to and designated as “the pair of braces 116”), a pair of knee flexion assembly 118a and 118b (hereinafter collectively referred to and designated as “the knee flexion assembly 118”), a hip flexion assembly 120a and 120b (hereinafter collectively referred to and designated as “the hip flexion assembly 120”), a back support 122, a pneumatic assembly 124, a treadmill 126, a display device 128, and a pelvis support 130.
In some aspects of the present disclosure, the pelvis support 130 may be actuated by means of pneumatics, electricity, hydraulics, or a combination thereof.
The communication network 131 established within the system 100 may ensure seamless interaction and coordination between all components, both mechanical and electronic. The communication network 131 may include suitable logic, circuitry, and interfaces that provide a plurality of network ports and communication channels for the transmission and reception of data related to the system's operations. Each network port is associated with a virtual address, such as an Internet Protocol Version 4 (IPv4) or IPv6 address, or a physical machine address, like a Media Access Control (MAC) address, facilitating efficient data exchange.
The communication network 131 may operate at various levels, including the application layer, where the communication network 131 implements communication protocols based on requests from different components of the system. These protocols include Hypertext Transfer Protocol (HTTP), File Transfer Protocol (FTP), Simple Mail Transfer Protocol (SMTP), Domain Name System (DNS) protocol, Common Management Interface Protocol (CMIP), Transmission Control Protocol and Internet Protocol (TCP/IP), User Datagram Protocol (UDP), Long Term Evolution (LTE) communication protocols, and others.
Data transmission and reception within the network occur over multiple communication channels, which can be either wireless, wired, or a combination of both. These channels adhere to data standards defined by various network types such as Local Area Network (LAN), Personal Area Network (PAN), Wireless Local Area Network (WLAN), Wireless Sensor Network (WSN), Wide Area Network (WAN), Wireless Wide Area Network (WWAN), Metropolitan Area Network (MAN), Satellite Network, Internet, Fiber Optic Network, Coaxial Cable Network, Infrared (IR) network, Radio Frequency (RF) network, among others. This comprehensive network infrastructure ensures that the system can leverage a broad spectrum of communication technologies, including future advancements.
The frame 102 may be adapted to provide a robust and stable platform where components of the system 100 may be securely mounted. Specifically, the frame 102 may be adapted to provide the robust and the stable platform where the back support 122, the pelvis support 130, the user interface 112, the treadmill 126, and the pair of braces 116 maybe securely mounted. The frame 102 may be further adapted to facilitate adjustability and customization that may allow healthcare professionals to tailor the system 100 to fit different user anatomies and rehabilitation needs that may further enhance comfort and optimize rehabilitation outcomes.
The base 104 may be adapted to provide a stable and secure foundation for the system 100. The base 104 may be designed to support the weight of the user and the mechanical components, ensuring balance and preventing any unwanted movement of the system 100 during operation.
The first set of sensors 106 may be coupled to the pair of braces 116 and configured to sense one or more matrices that may be associated with kinematics of the pair of braces 116. In some aspects of the present disclosure, the one or more metrices may include one of position, speed, acceleration, or any co, of the pair of braces 116. Aspects of the present disclosure are intended to include and/or otherwise cover all the metrices, without deviating from the scope of the present disclosure.
In some aspects of the present disclosure, the first set of sensors 106 may include, anyone, or a combination of, a position sensor, a speed sensor, an accelerometer, an electromyography (EMG) sensor, an Electroencephalography (EEG) sensor, and a force sensor. Aspects of the present disclosure are intended to include and/or otherwise cover all the sensors that may be configured to sense one or more metrices, without deviating from the scope of the present disclosure.
In some aspects of the present disclosure, the EMG sensors may be configured to detect and record the muscle activity and the EEG sensors may be configured to detect and record the brain signal activity of the user.
In some aspects of the present disclosure, the EEG sensor and the EMG may further be adapted to analyse the correct gait pattern.
In some aspects of the present disclosure, the input may be functional electrical stimulation that may be integrated with the pair of braces 116 during the gait training to enhance motor relearning process during the gait training.
The second set of sensors 108 may be configured to sense one or more variables that may be associated with the pneumatic assembly 124. In some aspects of the present disclosure, the one or more variables may include pressure applied by one or more pistons of the pneumatic assembly 124 (not shown), flow rate of gas in the pneumatic assembly 124, one or more position of the one or more pistons, and one or more electrical parameters. Aspects of the present disclosure are intended to include and/or otherwise cover all the variables, without deviating from the scope of the present disclosure.
In some aspects of the present disclosure, the one or more electrical parameters may include voltage and current, which may be utilized by the pneumatic assembly 124.
In some aspects of the present disclosure, the second set of sensors 108 may include a pressure sensor, a flow sensor, and a position sensor. Aspects of the present disclosure are intended to include and/or otherwise cover all the sensors that may be configured to sense the one or more variables, without deviating from the scope of the present disclosure.
The input unit 110 may be configured to enable a user to provide one or more physiological parameters and one or more gait parameters of a user. The input unit 110 may be further configured to enable a user to select one of a passive mode, an assistive mode, or an active mode. In some aspects of the present disclosure, the one or more physiological parameters may include, a body weight, a height, length of a leg, muscle strength, joint range of motion, body mass index (BMI), balance and coordination, neuromuscular control, posture, previous injuries, joint conditions, neurological conditions, cardiovascular fitness, orthopaedic conditions, muscle tone abnormalities, pain levels, circulatory issues, respiratory conditions, and medication effects. Aspects of the present disclosure are intended to include and/or otherwise cover all the physiological parameters, without deviating from the scope of the present disclosure. In some aspects of the present disclosure, the one or more gait parameters may include speed of walking, step length, ground clearance, and range of motion. Aspects of the present disclosure are intended to include and/or otherwise include all the gait parameters, without deviating from the scope of the present disclosure.
The user may select the one or more physiological parameters and the one or more gait parameters through the user interface 112.
The processing circuitry 114 may be coupled to the input unit 110, the first set of sensors 106, and the second set of sensors 108. The processing circuitry 114 may be configured to generate a gait pattern based on the one or more physiological parameters and the one or more gait parameters by way of an AI/ML technique or the one or more computational techniques.
In some aspects of the present disclosure, the gait pattern as mentioned herein may refer to a specific way in which the user walks, including the sequence and timing of movements, stride length, walking speed, and overall rhythm of the legs during walking. The gait pattern may encompass the coordinated actions of muscles and joints during each step, reflecting the unique walking style and biomechanics of the user. The processing circuitry 114 may be further configured to allow the pneumatic assembly 124 to actuate the pair of braces 116 based on the gait pattern, the one or more metrices and the one or more variables in any one of the passive mode, the assistive mode, or the active mode such that in the passive mode, the pair of braces 116 are actuated to move the legs of the user without any effort from the user, ii in the assistive mode, the pair of braces 116 are actuated to move the legs with supplemental assistance based on the efforts of the user, and in the active mode, the pair of braces 116 are actuated to provide adjustable resistance to the legs during movement of the legs.
The processing circuitry 114 may be further configured to update the gait pattern based on one or more changes in the one or more physiological parameters and the one or more gait parameters. The processing circuitry 114 may be further configured to generate an excursion pattern. Specifically, the processing circuitry 114 may be further configured to generate the excursion pattern based on the gait pattern generated. Further, the processing circuitry 114 may be configured to allow the pneumatic assembly (124) to actuate a back support (122) based on the excursion pattern to facilitate coordinated movement of the torso of the user in an upward direction and a downward direction with linear movement of knees, hips and ankle joints of the user.
In some aspects of the present disclosure, the back support (122) may be worn on the torso of the user by way of a harness. The harness may be designed to attach the users of different bodily parameters such as height, width, etc. The weight of the user may be distributed across the harness evenly.
In some aspects of the present disclosure, the gait pattern may also be generated or updated by employing visual sensors like camera, which may implement one or more image processing techniques to evaluate the gait pattern and thereby updating the gait pattern until the appropriate gait pattern may be generated. In some further aspects, the appropriate gait pattern may be sent to a doctor to understand the extent of improvement in the gait pattern.
In some aspects of the present disclosure, the input from the input unit 110 may be a functional electric stimulation that may be integrated with the pair of braces 116 during gait training to enhance motor relearning process during the gait training.
The pair of braces 116 (hereinafter also designated and referred to as “the braces 116”) may be coupled to the processing circuitry 114. The pair of braces 116 may be adapted to be worn on the legs of the user. The pair of braces 116 may be tied on the legs by way of straps (later shown in FIG. 1B). Each brace of the pair of braces 116 may be worn each leg of the user. The pair of braces 116 may be adapted to treat walking disability of the user. Each brace of the braces 116 may act as a leg orthosis for the user. Each brace of the pair of braces 116 may include the knee flexion assembly 118 and the hip flexion assembly 120. The knee flexion assembly 118 may be adapted to assist or control the bending and straightening movements of a knee of the user. The knee flexion assembly 118 may assist in providing support and stability to the knee during the gait training. The hip flexion assembly 120 may be adapted to assist or control the movements of a hip of the user. The hip flexion assembly 120 may provide a support and stability to the hip that may ensure a proper alignment of a pelvis region of the user. The hip flexion assembly 120 may also include a plurality of sensors to monitor the position and movement of a hip joint, enabling real-time adjustments to enhance the gait pattern and accommodate the user's specific needs.
The back support 122 may be coupled to the pair of braces 116 and the processing circuitry 114. The back support 122 may be adapted to support or hold the back of the user, while the user is walking on the system 100. Specifically, the back support 122 may be adapted to support the body weight of the user that may be adapted to allow the user to be in upright position during the walking. The back support 122 may exhibit vertical motion such that the back support 122 moves up and down. The vertical motion of the back support 122 may be synchronized with the walking pattern of the user.
In some embodiments, the vertical motion of the back support 122 may be follow an excursion pattern that may be generated by the AI technique.
In some aspects of the present disclosure, the back support 122 which may be supporting the body weight may be adapted to provide incremental or adjustable body weight support up on the user input.
In some aspects of the present disclosure, the walking pattern of the user as mentioned herein may refer to the specific sequence of movements and steps taken by the user while walking, which can be characterized by parameters such as stride length, walking speed, and the natural rhythm of the gait of the user.
The pneumatic assembly 124 may be coupled to the processing circuitry 114, the plurality of braces 116, and the back support 122. The pneumatic assembly 124 may be configured to control working of one of, the back-support 122, the braces 114, the treadmill 126, and the pelvis support 130. Specifically, the pneumatic assembly 124, based on the control signal that may be received from the processing circuitry 114, may be configured to control the working of the one of, the back-support 122, the braces 116, and the pelvis support 130. The pneumatic assembly 124 may include the piston that may be disposed in a cylinder such that the piston translates within the cylinder. The pneumatic device may further include a compressed air source that may facilitate actuation of the piston within the cylinder. The piston, upon actuation within the cylinder, may be adapted to control working of one of, the back-support 122, the pair of braces 114, the treadmill 126, and the pelvis support 130.
The treadmill 126 may be coupled to the processing circuitry 114. The treadmill 126 may be present over the base 104. The treadmill 126 may be adapted to facilitate the user to walk on the system 100. The speed of the treadmill 126 may be synchronized with the walking pattern of the user.
The secondary straps 127 may be adapted to hold the user when an emergency indicator indicates an emergency or failure of the one or more components of the system 100. The system 100 may include an emergency switch (not shown) which may be activated by the user. The system 100 may further include one or more cameras for the monitoring of the user undergoing training.
The display device 128 may be coupled to the frame 102 and the processing circuitry 114. The display device positioned in front of the user undergoing gait training. The display device 128 may act as a vital interface for interaction and monitoring throughout a session of the gait training. The display device 128 may provide real-time visual feedback on essential parameters such as step length, ground clearance, and walking speed, allowing the users to observe and adjust their performance to match the desired gait patterns. The users may dynamically modify the gait parameters during the session, adapting the training to their current rehabilitation phase or specific needs. The display device 128 may be further configured to facilitate a selection of the various exercise modes, including passive, active, assistive, and specific exercise modes. The display device 128 may provide immediate feedback on mode selection and performance metrics. Safety features and performance indicators, such as heart rate monitoring and joint force analysis, may also be displayed in real time to ensure users exercise within safe limits. Furthermore, the display device 128 may track and record the progress of the user over time, generating comprehensive reports based on each training session. The reports may include detailed performance metrics and improvements, which the users and healthcare providers may review to optimize training plans and monitor rehabilitation progress accurately. The display device 128 may be further configured to display real-time video animations to the user about the gait pattern and the walking patterns.
In some aspects of the present disclosure, the display device 128 may include any one of, a monitor, a LCD screen, an LCD screen, a virtual reality (VR) headset, an augmented reality (AR) headset, a holographic display, and a projector. Aspects of the present disclosure are intended to include and/or otherwise cover all the display devices, without deviating from the scope of the present disclosure.
The pelvis support 130 may be coupled to the frame 102. The pelvis support 130 may be adapted to facilitate a natural tilt of the pelvis of the user. Specifically, the pelvis support 130 may be adapted to facilitate the natural tilt of the pelvis of the user during walking and also support the back of the user. Additionally, the pelvis support 130 may be equipped with a plurality of springs that have tension adjustment capabilities to prevent drag and assist with foot drop conditions. To ensure maximum comfort, each strap of the pelvis support 130 may be cushioned adequately. Furthermore, the width of the pelvis, which is the gap between the legs, may be adjusted according to the width of the pelvis, providing a customizable fit.
In operation, the system 100 by way of the first set of sensors 106 strategically placed to capture the one or more matrices related to the movement of braces 116 monitors parameters such as one of the joint position, the speed, or the acceleration to provide real-time data for the system 100. Simultaneously, the system 100 by way of the second set of sensors 108 monitors the one or more variables associated with the pneumatic assembly 124 to supply necessary power for the movement of the braces 116. The system 100 by way of the input unit 110 may be configured to receive the one or more physiological parameters and the one or more gait parameters from the user, allowing selection of operation modes the passive mode, the assistive mode, or the active mode based on the capabilities and the needs of the user. The processing circuitry 114 may generate the gait pattern by implementing the one or more artificial intelligence (AI) techniques or one or more machine learning (ML) technique. The system by way of the processing circuitry may further be configured to generate a gait pattern and allow the pneumatic assembly 124 to actuate the pair of braces 116 based on the gait pattern, the one or more metrices and the one or more variables in any one of the passive modes, the assistive mode, or the active mode. In the passive mode, the pair of braces 116 are actuated to move the legs of the user without any effort from the user. In the assistive mode, the pair of braces (116) are actuated to move the legs with supplemental assistance based on the efforts of the user. In the active mode, the pair of braces 116 are actuated to provide adjustable resistance to the legs during movement of the legs. Further, the system 100 by way of the processing circuitry 114 is configured to update the gait pattern in real time based on one or more changes in the one or more physiological parameters and the one or more gait parameters. Furthermore, the system 100 by way of the processing circuitry 114 is configured to generate an excursion pattern based on the gait pattern by way the AI/ML technique or the one or more computational techniques to allow the pneumatic assembly 124 to actuate the back support 122 to facilitate coordinated movement of the torso of the user in an upward direction and a downward direction with linear movement of the knees, the hips, and the ankle joints of the user.
FIG. 1B illustrates a block diagram of the system 100, in accordance with an aspect of the present disclosure.
The system 100 may be driven by the pneumatic assembly 124. The pneumatic assembly 124 may supply the power to the braces 116. The braces 116 may be worn on the legs by the user. Specifically, the braces 116 may be worn on the legs of the user for the gait training by following the gait pattern. The gait pattern that may be generated by the processing circuitry 114 may facilitate the braces 116 in the gait pattern that may mimic the natural walking pattern of the user. The pneumatic assembly 124 may be adapted to provide the required power for the movement of the braces 116. The pneumatic assembly 124 may generate the power by using the compressed gas. In some embodiments of the present disclosure, the compressed gas may be compressed air. The compressed gas may be stored in reservoirs or tanks that may be present in the system 100. When the system 100 is activated, a plurality of valves (not shown) which may be controlled by the processing circuitry 114 releases the compressed gas stored in the reservoirs into actuators that may be located at the knee flexion assembly 118 and the hip flexion assembly 120. The actuators may convert the energy generated by the gas (pneumatic energy) into mechanical motion, thereby enabling the braces 116 to move according to the gait pattern. The pressure and the flow of the compressed air may be regulated by the second set of sensors 108 and the one or more computational techniques to facilitate the movement replicating the natural human walking pattern. The system 100 may include a plurality of passive supports to provide stability and issues related to a foot of the user such as a foot drop during walking on the treadmill 126.
The gait pattern may be generated by the processing circuitry 114. The gait pattern may replicate the natural walking pattern of the user. The gait pattern may be generated based on the one or more physiological parameters and the one or more gait patterns. The one or more gait patterns may be adjusted in the real-time. For each adjustment, the processing circuitry 114 may be configured to generate the updated gait pattern. In simpler words, the processing circuitry 114 may be configured to generate the updated gait pattern with each real-time adjustment that may be made. The processing circuitry 114 may be configured to generate the gait pattern by implementing one or more artificial intelligence (AI) techniques. Specifically, the processing circuitry 114 may be configured to generate the gait pattern by implementing one or more mathematical models associated with the walking patterns of the user and the one or more gait parameters.
The back support 122 (also called body weight support) may be adapted to maintain a posture of the user during walking on the treadmill 126. The back support 122 may be in synchronization with the braces 116. The processing circuitry 114 may be configured to generate the excursion pattern for the movement of the back of the user in synchronization with the walking pattern of the user. For example, when the user takes a step and their leg moves forward, the actuators at the hip and knee joints adjust the leg position. Simultaneously, the back support moves up and down in sync with the leg movements, maintaining proper posture and balance. This synchronized movement mimics the natural rise and fall of the torso during walking, helping users maintain stability and reducing the risk of injury. By matching the vertical movements of the back support with the leg motions, the system offers a more comfortable and natural walking experience, essential for effective gait training and rehabilitation. The processing circuitry 114 may implement one or more AI techniques to generate the excursion pattern.
In some aspects of the present disclosure, the excursion pattern may be generated from feedback of the first set of sensors 106, second set of sensors 108, one or more physiological parameters and the one or more gait parameters. Specifically, the excursion pattern may be generated based on the gait pattern generated.
The processing circuitry 114 may be configured to control the movement of the braces 116 and the back support 122. The gait pattern and the excursion pattern may be updated in a continual manner based on the feedback from the first and the second set of sensors 106 and 108. The first and second set of sensors 106 and 108 may provide real-time feedback to the processing circuitry 114 for the generating and updating the gait pattern and the excursion pattern. The processing circuitry 114 may be configured to manage subtle disturbances during walking that may arise due to medical conditions of the user. The processing circuitry 114 may be further configured to handle various modes of the system 100. The various modes may include, the passive mode, the assistive mode and the active mode.
In some embodiments of the present disclosure, the processing circuitry 114 may gather real-time feedback from the first and second set of sensors 106 and 108. The processing circuitry 114 may compare the gait pattern generated based on the readings of the first and second set of the sensors 106 and 108 with a desired gait pattern. In some aspects of the present disclosure the desired gait pattern may be the pattern that may be generated based on the based on the physiological and the gait parameters of the user. When the pattern that may be generated from the readings of the first and the second set of sensors 106 and 108 (hereinafter referred to and designated as “the gait pattern”) matches with the desired gait pattern, the processing circuitry 114 may maintain the current settings and operations of the system 100. When the gait pattern mismatches with the desired gait pattern then the processing circuitry 114 may be configured to identify deviations between both the patterns (actual and desired gait pattern). The deviations may include disturbances, resistance from the user or any other anomalies that may be affecting the movement of the user on the treadmill 126. The processing circuitry 114 may employ the one or more AI techniques for the adjustment of the actual gait parameters such that the gait parameters match with the desired gait pattern. The one or more adjustments may include alteration of joint positions, speeds, or forces. The processing circuitry 114 may continuously monitor the feedback and makes iterative adjustments to minimize the deviation and ensure the gait pattern is as accurate as possible. This dynamic correction process may enhance the ability of the system 100 to provide effective gait training and rehabilitation.
The processing circuitry 114 may be configured to track one or more attributes of the user undergoing the gait training. The one or more attributes may include, the physiological parameters, positional data, user efforts, the gait parameters, the one or more metrices, the one or more variables, and emergency indicators. Aspects of the present disclosure are intended to include and/or otherwise include all the attributes, without deviating from the scope of the present disclosure. FIG. 1C illustrates the braces 116 of the system 100 of FIG. 1, in accordance with an aspect of the present disclosure.
The pair of braces 116 may be adapted to be worn on the legs of the user. The pair of braces 116 may be tied on the legs by way of straps 138. Each brace of the pair of braces 116 may be worn each leg of the user. Each brace of the pair of braces 116 may be adapted to support or hold each leg of the legs of the user. Specifically, the braces 116 may be adapted to treat walking disability of the user. Each brace of the braces 116 may act as a leg orthosis for the user. Each brace of the pair of braces 116 may include the knee flexion assembly 118 and the hip flexion assembly 120. Each brace of the braces 116 may act as a leg orthosis for the user. Each brace of the pair of braces 116 may include the knee flexion assembly 118 and the hip flexion assembly 120. The knee flexion assembly 118 may be adapted to assist or control the bending and straightening movements of a knee of the user. The knee flexion assembly 118 may assist in providing support and stability to the knee during the gait training.
The pair of braces 116 may include an upper arm 134 and a lower arm 136. The lower arm 136 may be fixed to the upper arm 134. Specifically, the lower arm 136 may be fixed to the upper arm 134 by way of a pivot bolt 140. The pivot bolt 140 may facilitate the movement of the lower arm 136 with respect to the upper arm 134.
The knee flexion assembly 118 and the hip flexion assembly 120 each feature a threaded hole (not shown) to receive a pivot bolt 140. The pivot bolt 140 has a threaded section that can be tightened into the flexion assemblies (knee flexion assembly and the hip flexion assembly). The lower arm 136 is equipped with multiple vertically aligned holes, allowing for precise height adjustment. By inserting the pivot bolt 140 into different holes on the lower arm 136, the height of the flexion assemblies may be adjusted.
The knee flexion assembly 118 and the hip flexion assembly 120 may include a support plate 139. The knee flexion assembly 118 and the hip flexion assembly 120 each include the support plate 139. The support plate 139 may be equipped with the straps 138 that may be attached to the support plate 139. The straps 138 may be wrapped around the legs and the hips of the user. Once in place, the straps can be tightened to secure the support plate firmly against the body, ensuring that the leg and hip are held securely within each brace.
FIG. 1D illustrates a perspective view of the gait training system 100 of FIG. 1, in accordance with an aspect of the present disclosure.
The system 100 may include a plurality of handles 142. The plurality of handles 142 may be positioned along the frame 102 to provide the users with point of contact and support. The plurality of handles 142 (hereinafter referred and designated as “the handles”) may assist the user performing the gait exercises in maintaining balance and stability during walking. The handles 142 may be fixed to the frame 102 by bolts and clamps. The handles 142 may be adjusted to different positions.
The handles 142 may be fixed to a pair of rods 144. The pair of rods 144 may be affixed to the base 104 of the frame 102 using adjustable mounts that may facilitate vertical movement of the pair rods 144. The vertical movement of the pair of rods 144 may facilitate the handles 142 attached to the pair of rods 144 to be adjusted according to the height of the user. For users of shorter stature, the pair of rods 144 may be lowered, positioning the handles 142 within easy reach. Conversely, taller users may raise the rods to achieve a comfortable height. An adjustment of the handles 142 by sliding the rods vertically along tracks or grooves integrated into the frame 102 may ensure smooth and precise positioning of the handles 142.
In some aspects of the present disclosure, the pair of rods 144 may also be actuated automatically based on user input from the user interface 112. Through the user interface 112, the user may specify their height or preferred handle position electronically. The input may trigger automated mechanisms within the frame 102 that may adjust the pair of rods 144 accordingly.
FIG. 2 illustrates a block diagram of the processing circuitry 114 of the system 100 of FIG. 1, in accordance with an aspect of the present disclosure.
The processing circuitry 114 may implement a pattern generation engine 202, a control engine 204, a mode control engine 206, and a flexion pattern generation engine 208. The pattern generation engine 202, the control engine 204, the mode control engine 206, and the flexion pattern generation engine 208 may be communicatively coupled to each other by way of a communication bus 210.
The pattern generation engine 202 may be configured to generate the gait pattern based on the physiological parameters and the gait parameters and the real-time adjustments made in the physiological parameters and the gait parameters via the user interface. The gait pattern generation engine 202 may implement artificial intelligence (AI)/machine learning (ML) techniques that may be trained on human gait data to dynamically adjust the pattern to mimic patterns of natural walking. The pattern generation engine 202 may further be configured to generate the excursion pattern based on the gait pattern by way the AI/ML technique or the one or more computational techniques. The gait pattern generation engine 202 may further be configured to update the gait pattern and the excursion pattern based on changes in the the one or more physiological parameters and the one or more gait parameters. The gait pattern generation engine 202 may further be configured to transmit the gait pattern and the excursion pattern to the control engine 204.
The control engine 204 may be configured to receive the gait pattern and the excursion pattern from pattern generation engine 202. Further, the control engine 204 may be configured to manage the operation of the pair of braces 116. The control engine 204 may be further configured to facilitate coordination of the pair of braces 116 to ensure accurate movement of the legs by enabling the pneumatic assembly 124 to actuate the pair of braces 116 based on the gait pattern, the one or more metrices and the one or more variables. Specifically, the control engine 204 may be further configured to allow the pneumatic assembly 124 to actuate the pair of braces 116 in one of a passive mode, an assistive mode, or an active mode. Furthermore, the control engine 204 may be further configured to allow the pneumatic assembly 124 to actuate the back support 122 to facilitate coordinated movement of the torso of the user in the upward direction and the downward direction with linear movement of the knees, the hips, the ankle joints of the user.
The mode control engine 206 may govern the operation modes that may be available to the user:- the passive, the assistive, and the active modes. In the passive mode, the model control engine 206 may autonomously control the movement of the legs without the efforts of the user. In the assistive mode, the processing circuitry 114 may adjust support based on user input to aid natural movement of the user. The active mode may introduce resistance to challenge and strengthen the muscles of the user. Inside the processing circuitry 114, the mode control engine 206 may manage the transitions of the modes of operation that may interpret the user input from the interface panel, and adjusts parameters accordingly.
The flexion pattern generation engine 208 may be configured to generate the flexion patterns through data acquisition, processing, and real-time adjustments. The flexion pattern generation engine 208 may interface with the first set of sensors 106 at the knee and hip joints to collect data on joint angles, velocities, and forces. The flexion pattern generation engine 208 may run a technique to process the data using biomechanical models and machine learning to determine optimal flexion and extension angles for a natural gait cycle. The processing circuitry 114 may implement calculations to send control signals to the actuators, adjusting joint positions accordingly.
FIG. 3 illustrates a method 300 of gait training by the system 100 of the FIG. 1, in accordance with an aspect of the present disclosure.
At step 302, the system 100 may be configured to receive the one or more physiological parameters and the one or more gait parameters. Specifically, the system 100 may be configured to receive the one or more physiological parameters and the one or more gait parameters, by way of the input unit 110.
At step 304, the system 100 may be configured to generate the gait pattern. Specifically, the system 100 may be configured to generate the gait pattern by way of the processing circuitry 114 via an AI/ML technique or the one or more computational techniques, wherein the gait pattern is based on one or more physiological parameters and one or more gait parameters provided to the input unit 114.
At step 306, the system 100 may be configured to allow pneumatic assembly 124 coupled to the pair of braces 116 adapted to be worn on the legs of the user to actuate the pair of braces 116 to move the legs of the user based on the gait pattern, the one or more matrices sensed by the first set of sensors 106 coupled to the pair of braces 116, and the one or more variables sensed by the second set of sensors 108 coupled to the pneumatic assembly 124 in any one of the passive mode, the assistive mode, or the active mode. Further, in the passive mode, the pair of braces 116 are actuated to move the legs of the user without any effort from the user. In the assistive mode, the pair of braces 116 are actuated to move the legs with supplemental assistance based on the efforts of the user. In the active mode, the pair of braces 116 are actuated to provide adjustable resistance to the legs during movement of the legs.At step 308, the system 100 may be configured to generate an excursion pattern based on the gait pattern via the AI/ML technique or the one or more computational techniques; and allow the pneumatic assembly 124 to actuate the back support 122 that is coupled to the pair of braces 116 and the pneumatic assembly 124 and adapted to be worn on torso of the user, to facilitate coordinated movement of the torso of the user in an upward direction and a downward direction with linear movement of the knees, the hips, and the ankle joints of the user.
At step 310, the system 100 may be configured to update the gait pattern in real time based on one or more changes in the one or more physiological parameters and the one or more gait parameters.
The foregoing discussion of the present disclosure has been presented for purposes of illustration and description. It is not intended to limit the present disclosure to the form or forms disclosed herein. In the foregoing Detailed Description, for example, various features of the present disclosure are grouped together in one or more aspects, configurations, or aspects for the purpose of streamlining the disclosure. The features of the aspects, configurations, or aspects may be combined in alternate aspects, configurations, or aspects other than those discussed above. This method of disclosure is not to be interpreted as reflecting an intention the present disclosure requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed aspect, configuration, or aspect. Thus, the following claims are hereby incorporated into this Detailed Description, with each claim standing on its own as a separate aspect of the present disclosure.
Moreover, though the description of the present disclosure has included description of one or more aspects, configurations, or aspects and certain variations and modifications, other variations, combinations, and modifications are within the scope of the present disclosure, e.g., as may be within the skill and knowledge of those in the art, after understanding the present disclosure. It is intended to obtain rights which include alternative aspects, configurations, or aspects to the extent permitted, including alternate, interchangeable and/or equivalent structures, functions, ranges or steps to those claimed, whether or not such alternate, interchangeable and/or equivalent structures, functions, ranges or steps are disclosed herein, and without intending to publicly dedicate any patentable subject matter.
Certain terms are used throughout the following description and claims to refer to particular features or components. As one skilled in the art will appreciate, different persons may refer to the same feature or component by different names. This document does not intend to distinguish between components or features that differ in name but not structure or function. While various aspects of the present disclosure have been illustrated and described, it will be clear that the present disclosure is not limited to these aspects only. Numerous modifications, changes, variations, substitutions, and equivalents will be apparent to those skilled in the art, without departing from the spirit and scope of the present disclosure, as described in the claims. ,CLAIMS:1. A system (100) comprising:
a pair of braces (116) adapted to be worn on legs of a user;
a first set of sensors (106) that are coupled to the pair of braces (116) and configured to sense one or more metrices that are associated with kinematics or kinetic of the pair of braces (116);
a pneumatic assembly (124) that is coupled to the pair of braces (116) and configured to actuate the pair of braces (116) to move the legs of the user;
a second set of sensors (108) that are coupled to the pneumatic assembly (124) and configured to sense one or more variables that are associated with the pneumatic assembly (124);
an input unit (110) configured to: (i) receive one or more physiological parameters of the user, and (ii) one or more gait parameters associated with the user; and
processing circuitry (114) coupled to the first set of sensors (106), the second set of sensors (108), and the input unit (110) and configured to: (i) generate a gait pattern based on the one or more physiological parameters and the one or more gait parameters by way of an AI/ML technique or one or more computational techniques and (ii) allow the pneumatic assembly (124) to actuate the pair of braces (116) based on the gait pattern, the one or more metrices and the one or more variables in any one of a passive mode, an assistive mode, or an active mode such that (i) in the passive mode, the pair of braces (116) are actuated to move the legs of the user without any effort from the user, (ii) in the assistive mode, the pair of braces (116) are actuated to move the legs with supplemental assistance based on the efforts of the user, and (iii) in the active mode, the pair of braces (116) are actuated to provide adjustable resistance to the legs during movement of the legs.
2. The system as claimed in claim 1, wherein the processing circuitry (114) is further configured to update the gait pattern in real time based on one or more changes in the one or more physiological parameters and the one or more gait parameters.

3. The system (100) as claimed in claim 1, wherein the one or more gait parameters comprising, one of (i) speed of walking, (ii) step length, (iii) ground clearance, (iv) range of motion, or (v) acceleration.

4. The system (100) as claimed in claim 1, wherein the one or more physiological parameters comprising any one of, or a combination of, a body weight, a height of the user, a length of a leg, muscle strength, range of motion of a joint, body mass index (BMI), balance and coordination, neuromuscular control, spasms, previous injuries, joint conditions, neurological conditions, cardiovascular fitness, orthopedic conditions, muscle tone abnormalities, pain levels, circulatory issues, respiratory conditions, or medication effects.

5. The system (100) as claimed in claim 1, wherein the one or more metrices comprising, one of, a position, speed, or acceleration of the pair of braces (116).

6. The system (100) as claimed in claim 1, wherein the one or more variables comprising, one of (i) one or more pressure applied by one or more pistons of the pneumatic assembly, (ii) a flow rate of gas in the pneumatic assembly, (iii) one or more positions of the one or more pistons in the pneumatic assembly, and (iv) one or more electrical parameters.

7. The system (100) as claimed in claim 1, further comprising a back support (122) that is coupled to the pair of braces (116) and the pneumatic assembly (124) and adapted to be worn on torso of the user.

8. The system (100) as claimed in claim 1, wherein the processing circuitry (114) is further configured to generate an excursion pattern based on the gait pattern by way the AI/ML technique or the one or more computational techniques to allow the pneumatic assembly (124) to actuate the back support (122) to facilitate coordinated movement of the torso of the user in an upward direction and a downward direction with linear movement of knees, hips, and ankle joints of the user.

9. A method (300) comprising:
receiving (302), by way of the input unit (110), one or more physiological parameters of a user and one or more gait parameters associated with the user;
generating (304), by way of processing circuitry (114) coupled to a first set of sensors (106), a second set of sensors (108), and the input unit (110), a gait pattern via an AI/ML technique or the one or more computational techniques, wherein the gait pattern is based on one or more physiological parameters and one or more gait parameters provided to the input unit (114);
allowing (306), by way of the processing circuitry (114), a pneumatic assembly (124) coupled to a pair of braces (116) adapted to be worn on legs of a user to actuate the pair of braces (116) to move the legs of the user based on the gait pattern, one or more matrices sensed by the first set of sensors (106) coupled to the pair of braces (116), and one or more variables sensed by the second set of sensors (108) coupled to the pneumatic assembly (124) in any one of a passive mode, an assistive mode, or an active mode such that (i) in the passive mode, the pair of braces (116) are actuated to move the legs of the user without any effort from the user, (ii) in the assistive mode, the pair of braces (116) are actuated to move the legs with supplemental assistance based on the efforts of the user, and (iii) in the active mode, the pair of braces (116) are actuated to provide adjustable resistance to the legs during movement of the legs; and
generating (308), by way of the processing circuitry (114), an excursion pattern based on the gait pattern via the AI/ML technique or the one or more computational techniques; and allow the pneumatic assembly (124) to actuate a back support (122) that is coupled to the pair of braces (116) and the pneumatic assembly (124) and adapted to be worn on torso of the user, to facilitate coordinated movement of the torso of the user in an upward direction and a downward direction with linear movement of knees, hips, and ankle joints of the user;.

10. The method (300) as claimed in claim 7, further comprising updating (310), by way of the processing circuitry (114), the gait pattern in real time based on one or more changes in the one or more physiological parameters and/or the one or more gait parameters.