Claims:1. A method of determining personalised ultrafiltration rate for a subject during dialysis, the method comprising:
projecting, by a first Light Emitting Diode (LED) source (109) configured in an ultrafiltration Rate (UFR) determination device (101), light rays to a blood sample flowing through a blood flow tube (103) into a dialyser (105) of a dialysis apparatus (200);
receiving, by a first photodiode sensor (111) configured in the UFR determination device (101), a first set of transmitted light rays based on the light rays projected from the first LED source (109);
projecting, by a second LED source (115) configured in the Ultrafiltration Rate (UFR) determination device (101), light rays to the blood sample flowing through the blood flow tube (103) out of the dialyser (105);
receiving, by a second photodiode sensor (117) configured in the UFR determination device (101), a second set of transmitted light rays based on the light rays projected from the second LED source (115);
detecting, by the first photodiode sensor (111) and the second photodiode sensor (117), a first set of signals and a second set of signals indicative of haemoglobin concentration in the blood sample based on the first set of transmitted light rays and the second set of transmitted light rays, respectively;
identifying, by the UFR determination device (101), variations in haemoglobin concentration of the blood sample based on the first set of signals and the second set of signals; and
determining, by the UFR determination device (101), the ultrafiltration rate for the subject based on the identified variations.

2. The method as claimed in claim 1 further comprising of converting, by a signal convertor (113), the first set of signals and the second set of signals into digital signals.

3. The method as claimed in claim 1, wherein the first LED source (109) and the second LED source (115) are a near infrared LED source.

4. An ultrafiltration rate (UFR) determination device (101) for determining personalised ultrafiltration rate for a subject during dialysis, the UFR determination device (101) comprising:

a first Light Emitting Diode (LED) source (109) for projecting light rays to a blood sample flowing through a blood flow tube (103) into a dialyser (105) of a dialysis apparatus (200);
a first photodiode sensor (111) for receiving a first set of transmitted light rays based on the light rays projected from the first LED source (109);
a second LED source (115) for projecting light rays to the blood sample flowing through the blood flow tube (103) out of the dialyser (105);
a second photodiode sensor (117) for receiving a second set of transmitted light rays based on the light rays projected from the second LED source (115), wherein the first photodiode sensor (111) and the second photodiode sensor (117) detect a first set of signals and a second set of signals indicative of haemoglobin concentration in the blood sample based on the first set of transmitted light rays and the second set of transmitted light rays, respectively; and
a computing unit (121) for identifying variations in haemoglobin concentration of the blood sample based on the first set of signals and the second set of signals, wherein the ultrafiltration rate for the subject is determined based on the identified variations.

5. The ultrafiltration rate (UFR) determination device (101) as claimed in claim 4 comprises a signal convertor (113, 119) for converting the first set of signals and the second set of signals into digital signals.

6. The ultrafiltration rate (UFR) determination device (101), as claimed in claim 4, wherein the first LED source and the second LED source are a near infrared LED source.

7. A dialysis apparatus (200) for providing personalised dialysis to subject, the dialysis apparatus (200) comprises:
a dialysing sensing device (201) comprising:
a support structure (219) in which the subject is laid down during dialysis;
an Electrocardiography (ECG) acquisition unit (211) connected to the subject through one or more ECG electrodes for acquiring ECG signals of the subject;
a Blood Pressure (BP) and Ballistocardiography (BCG) signal acquisition unit (213) connected to the subject for monitoring the BP of the subject;
a Photoplethysmography (PPG) signal acquisition unit (215) connected to a PPG sensor attached to the subject for monitoring urea in blood of the subject; and
a weight acquisition unit (217) comprising one or more sensors connected to the subject for monitoring weight of the subject;
an extracorporeal blood circuitry (203) connected to the subject for drawing blood sample from the subject for ultrafiltration and pushing back to the subject;
a dialysis fluid circuitry (205) configured for preparing dialysate solution;
a dialyser (105) connected to the dialysis fluid circuitry for receiving the dialysate solution and the blood sample from the extracorporeal blood circuitry (203);
an optical spectral electrolyte estimation device (207) for estimating concentration of one or more electrolytes, in the blood sample;
a decision and control device (209) configured for receiving inputs from the ECG acquisition unit (211), the BP and BCG signal acquisition unit (213), the PPG signal acquisition unit (215) and the weight acquisition unit (217) to assist in dialysis; and
an Ultrafiltration Rate (UFR) determination device (101) for providing personalised UFR to the subject.

8. The dialysis apparatus (200) as claimed in claim 7 comprising computing volume of dialysate solution and/of blood sample for dialysis by:
setting flow rate of the dialysate solution in the dialyser as one of, less than or equal to the UFR determination for the subject;
configuring speed of ultrafiltration pump (UFP) more than speed of the UFR based on the set flow rate of the dialysate solution.
setting flow rate of the dialysate solution higher than flow rate of blood and lesser than the flow of the UFR;
configuring speed of dialysate pump based on the set flow rate;

setting flow rate of the blood sample more than flow rate of blood in venous valve;
setting flow rate of blood sample more than flow rate of blood in arterial valve;
configuring speed of blood pump based on blood flow rate in arterial valve;
computing volume of dialysate solution based on the flow rate of the dialyser, diameter of tubing and duration.; and
computing volume of blood sample based on the set flow rate of the blood, diameter of tubing and duration of flow.

9. The dialysis apparatus (200) as claimed in claim 7, wherein the optical spectral electrolyte estimation device (207) comprising:
a laser light source (531) which excites light beams on the blood sample drawn from a blood flow tube (103) attached to the dialyser (105);
a fibre optics tube (533) which provides optical signals based on the light beams;
a prism (535) which detects one or more spectrums based on the optical signals; and
a spectrograph detector (537) which estimates concentration of one or more electrolytes in the blood sample based on the one or more spectrums.

10. The dialysis apparatus (200) as claimed in claim 7 comprising estimating urea concentration in the blood sample by:
emitting light rays on to a blood flow tube arranged between a LED source and a photodiode detector;
converting the light rays projected from the LED source as digital PPG signals; and
estimating the urea concentration in the blood sample based on the PPG signals.
11. A method, an ultrafiltration rate (UFR) determination device and a dialysis apparatus for determining personalised ultrafiltration rate for a subject during dialysis as herein substantiated in the description along with accompanied drawings.
, Description:TECHNICAL FIELD
The present subject matter is related in general to haemodialysis, more particularly, but not exclusively to a method and device for determining personalised ultrafiltration rate for a subject.

BACKGROUND

In principle, haemodialysis is a process involving a mere removal of either excess fluid termed as “ultrafiltration” or removal of unwanted toxic substances termed as “hemofiltration” present in blood of a subject. Typically, ultrafiltration involves complex control system due to involvement of several physical and physiological parameters. It is well-known to achieve satisfactory ultrafiltration by maintaining dialysate flow higher than that of blood flow. During this procedure, while excess fluid in the blood is removable, rate of ultrafiltration is a critical factor, since rapid removal of water from the blood may traumatically affect the subject undergoing ultrafiltration.
Irrespective of either inter dialysis or intra dialysis process, continuous removal of the fluid from the subject would lead to either myocardial infarctions or many other cardiac related fatal issues, which demands to have a balance in either electrolytes parameters or physical parameters. In nutshell, it boils to two main kinds of requirements. First requirement being a need to maintain the balance in several dynamically varying personal blood electrolytes parameters such as, sodium, potassium, calcium, magnesium, chlorides, and the like which prompts changes in the myocardial level activity of body because of changes in electrolyte concentration during ultrafiltration. In case, if the changes reach to dyselectroletimea condition, removal of the fluid would result to a fatal condition for the subject. Second requirement being a need to dynamically monitor the physical parameters of the subject such as, blood volume, blood flow rates, arterial and venous blood pressure, air bubble in blood at venous junction point and the like. Typically, the ultrafiltration rate (UFR) is decided in the inter dialysis process based on assessment of amount of fluid in the blood before beginning of dialysis and estimation of the amount of fluid to be removed. Generally, it is known that fluid extraction ratio restricts either dialysis efficiency or increases dialysis duration, though it is typically fixed in practice.
Conventional methodologies in ultrafiltration may not vary the UFR in intra dialysis in real-time. Additionally, conventional ultrafiltration techniques do not provide provision for sensing electrolyte variations in the blood of the subject to maintain a balance or for alarming condition for safe dialysis. Further, the conventional ultrafiltration techniques do not provide monitoring body weight of the subject continually during dialysis, even though body weight is an important factor in evaluating the UFR.
The information disclosed in this background of the disclosure section is only for enhancement of understanding of the general background of the invention and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art already known to a person skilled in the art.
SUMMARY

In an embodiment, the present disclosure may relate to a method for determining personalised ultrafiltration rate for a subject during dialysis. The method includes projecting light rays to a blood sample flowing through a blood flow tube into a dialyser of a dialysis apparatus, receiving a first set of transmitted light rays based on the light rays projected from the first LED source. Further, the method comprises projecting light rays to the blood sample flowing through the blood flow tube out of the dialyser and receiving a second set of transmitted light rays based on the light rays projected from the second LED source. A first set of signals and a second set of signals indicative of haemoglobin concentration is detected in the blood sample based on the first set of transmitted light rays and the second set of transmitted light rays, respectively. The method includes identifying variations in haemoglobin concentration of the blood sample based on the first set of signals and the second set of signals and determining the ultrafiltration rate for the subject based on the identified variations.
In an embodiment, the present disclosure may relate to an Ultrafiltration Rate (UFR) determination device for determining personalised ultrafiltration rate for a subject during dialysis. The Ultrafiltration Rate (UFR) determination device comprises a first Light Emitting Diode (LED) source for projecting light rays to a blood sample flowing through a blood flow tube into a dialyser of a dialysis apparatus. Based on the light rays projected from the first LED source, a first set of transmitted light rays is received by a first photodiode sensor. Further, the UFR determination device comprises a second LED source for projecting light rays on to the blood sample flowing through the blood flow tube out of the dialyser. Based on the light rays projected from the second LED source, a second set of transmitted light rays is received by a second photodiode sensor. The first photodiode sensor and the second photodiode sensor detect a first set of signals and a second set of signals indicative of haemoglobin concentration in the blood sample based on the first set of transmitted light rays and the second set of transmitted light rays, respectively. Further, the UFR determination device comprises a computing unit for identifying variations in haemoglobin concentration of the blood sample based on the first set of signals and the second set of signals. The ultrafiltration rate for the subject is determined based on the identified variations.
In an embodiment, the present disclosure may relate to a dialysis apparatus for providing personalised dialysis to subject. The dialysis apparatus includes a dialysing sensing device comprising a support structure in which the subject is laid down during dialysis, an Electrocardiography (ECG) acquisition unit connected to the subject through one or more ECG electrodes for acquiring ECG signals of the subject, a Blood Pressure (BP) and Ballistocardiography (BCG) signal acquisition unit connected to the subject for monitoring the BP of the subject, a Photoplethysmography (PPG) signal acquisition unit connected to a PPG sensor attached to the subject for monitoring urea in blood of the subject and a weight acquisition unit comprising one or more sensors connected to the subject for monitoring weight of the subject. Further, the dialysis apparatus includes an extracorporeal blood circuitry connected to the subject for drawing blood sample from the subject for ultrafiltration and feeding back to the subject, a dialysis fluid circuitry configured for preparing dialysate solution, a dialyser connected to the dialysis fluid circuitry for receiving the dialysate solution and the blood sample from the extracorporeal blood circuitry, an optical spectral electrolyte estimation device for estimating the concentration of one or more electrolytes, especially sodium ion and phosphate in the blood sample, a decision and control device configured for receiving inputs from the ECG acquisition unit, the BP and BCG signal acquisition unit, the PPG signal acquisition unit and the weight acquisition unit to assist in dialysis and an Ultrafiltration Rate (UFR) determination device for providing personalised UFR to the subject.

The foregoing summary is illustrative only and is not intended to be in any way limiting. In addition to the illustrative aspects, embodiments, and features described above, further aspects, embodiments, and features will become apparent by reference to the drawings and the following detailed description.

BRIEF DESCRIPTION OF THE ACCOMPANYING DRAWINGS
The accompanying drawings, which are incorporated in and constitute a part of this disclosure, illustrate exemplary embodiments and, together with the description, serve to explain the disclosed principles. In the figures, the left-most digit(s) of a reference number identifies the figure in which the reference number first appears. The same numbers are used throughout the figures to reference like features and components. Some embodiments of system and/or methods in accordance with embodiments of the present subject matter are now described, by way of example only, and with reference to the accompanying figures, in which:

Fig.1 illustrates an exemplary environment for determining personalised ultrafiltration rate for a subject during dialysis in accordance with some embodiments of the present disclosure;

Fig.2a illustrates an exemplary dialysis apparatus for providing personalised dialysis to subject in accordance with some embodiments of the present disclosure;

Fig.2b shows an exemplary representation of dialysis sensing device in accordance with some embodiments of the present disclosure;

Fig.3a illustrates a flowchart showing a method for computing volume of dialysate solution and of blood sample for dialyse in accordance with some embodiments of present disclosure;

Fig.3b illustrates a flowchart showing a method for reconfiguring speed of UFR pump in accordance with some embodiments of present disclosure;

Fig.4 shows an exemplary representation of estimating urea concentration in the blood sample in accordance with some embodiments of present disclosure;

Fig.5a shows an exemplary flowchart detecting electrolytes imbalance conditions in accordance with some embodiments of present disclosure;

Fig.5b shows an exemplary representation of estimating concentration of one or more electrolytes in the blood sample in accordance with some embodiments of present disclosure;

Fig. 5c shows an exemplary representation of estimating concentration of electrolytes in dialysate sample in accordance with some embodiments of present disclosure;

Fig.6a and Fig.6b show exemplary representations of inter-dialytic ultrafiltration rate controller and intradialytic ultrafiltration rate controller respectively in accordance with some embodiments of present disclosure;

Fig.6c shows an exemplary representation of inter and intra-dialytic ultrafiltration rate controller in accordance with some embodiments of present disclosure;

Fig.7a and Fig.8 shows exemplary representations of inter-dialytic ultrafiltration rate controller and intradialytic ultrafiltration rate controller respectively in accordance with some embodiments of present disclosure; and

Fig.9 illustrates a flowchart showing a method for determining personalised ultrafiltration rate for a subject during dialysis in accordance with some embodiments of the present disclosure.

It should be appreciated by those skilled in the art that any block diagrams herein represent conceptual views of illustrative systems embodying the principles of the present subject matter. Similarly, it will be appreciated that any flow charts, flow diagrams, state transition diagrams, pseudo code, and the like represent various processes which may be substantially represented in computer readable medium and executed by a computer or processor, whether or not such computer or processor is explicitly shown.

DETAILED DESCRIPTION

In the present document, the word "exemplary" is used herein to mean "serving as an example, instance, or illustration." Any embodiment or implementation of the present subject matter described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments.

While the disclosure is susceptible to various modifications and alternative forms, specific embodiment thereof has been shown by way of example in the drawings and will be described in detail below. It should be understood, however that it is not intended to limit the disclosure to the particular forms disclosed, but on the contrary, the disclosure is to cover all modifications, equivalents, and alternative falling within the scope of the disclosure.

The terms “comprises”, “comprising”, or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a setup, device or method that comprises a list of components or steps does not include only those components or steps but may include other components or steps not expressly listed or inherent to such setup or device or method. In other words, one or more elements in a system or apparatus proceeded by “comprises… a” does not, without more constraints, preclude the existence of other elements or additional elements in the system or method.

In the following detailed description of the embodiments of the disclosure, reference is made to the accompanying drawings that form a part hereof, and in which are shown by way of illustration specific embodiments in which the disclosure may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the disclosure, and it is to be understood that other embodiments may be utilized and that changes may be made without departing from the scope of the present disclosure. The following description is, therefore, not to be taken in a limiting sense.

Embodiments of the present disclosure relate to a method and an Ultrafiltration Rate (UFR) determination device for determining personalised Ultrafiltration Rate (UFR) for a subject during dialysis. Typically, existing dialysis systems may not periodically sense reduction of fluid in blood of the subject while performing ultrafiltration. Also, the existing dialysis systems during ultrafiltration process do not sense electrolytes variations in the blood for controlling balance or alarming for safety dialysis process. The present disclosure provides the UFR determination device for determining personalised Ultrafiltration Rate (UFR) for a subject during dialysis. Typically, light rays are projected to a blood sample of the subject which is flowing through a blood flow tube into a dialyser of a dialysis apparatus. A first set of light rays transmitted based on the light rays are received. Similarly, light rays are projected to the blood sample flowing through the blood flow tube out of the dialyser and corresponding second set of transmitted light rays are received. Based on the first set of transmitted light rays and the second set of transmitted light rays, a first set of signals and a second set of signals are detected which indicate haemoglobin concentration in the blood sample. Thus, the present disclosure identifies variations in haemoglobin concentration of the blood sample based on the first set of signals and the second set of signals. Thereby, the UFR is determined for the subject based on the identified variations.

Fig.1 illustrates an exemplary environment for determining personalised ultrafiltration rate for a subject during dialysis in accordance with some embodiments of the present disclosure.

Fig.1 shows an Ultrafiltration Rate (UFR) determination device 101. The UFR determination device 101 includes a blood flow tube 103 passing through a dialyser 105. In an embodiment, the dialyser 105 is an apparatus in which dialysis is carried out. The dialyser 105 consists of essentially one or more containers for liquids separated into compartments by membranes. The dialyser 105 includes blood sample 107 of a subject undergoing ultrafiltration process. Further, the UFR determination device 101 includes a first Light Emitting Diode (LED) source 109, a first photodiode sensor 111 and a first signal converter 113 placed at one end of the blood flow tube 103 from where blood sample 107 passes into the dialyser 105. Similarly, the UFR determination device 101 includes a second Light Emitting Diode (LED) source 115, a second photodiode sensor 117 and a second signal converter 119 placed at other end of the blood flow tube 103 from where blood sample 107 flows out of the dialyser 105. Further, the UFR determination device 101 includes a computing unit 121. In an embodiment, the UFR determination device 101 is part of a dialysis apparatus as explained below in Fig.2a. In an embodiment, the first LED source 109 and the second LED source 115 are a near infrared LED source, for example.

When the blood sample 107 of the subject is passed through the dialyser 105 for ultrafiltration, light rays are passed by the first LED source 109 to the blood sample 107 which is flowing through the blood flow tube 103 into the dialyser 105. In an embodiment, the first LED source 109 may provide light rays of various wavelengths. For example, wavelength is approximately equal to 810nm. On projecting the light rays, the first photodiode sensor 111 may receive a first set of transmitted light rays based on the projected light rays from the first LED source 109.On receiving the first set of transmitted light rays and once the blood sample passes out of the dialyser 105, light rays are passed by the second LED source 115 to the blood sample 107.
On projecting the light rays, the second photodiode sensor 117 may receive a second set of transmitted light rays based on the projected light rays from the second LED source 115. Further, the first photodiode sensor 111 and the second photodiode sensor 117 may determine a first set of signals and a second set of signals based on the first set of transmitted light rays and the second set of transmitted light rays respectively. Particularly, the first set of signals and the second set of signals indicate haemoglobin concentration in the blood sample 107 of the subject. Further, the first signal converter 113 and the second signal converter 119 may convert the first set of signals and the second set of signals respectively into digital signals. Thus, based on the first set of signals and the second set of signals, the computing unit 121 may detect variations in the haemoglobin concentration of the blood sample 107. Thereafter, based on the variations, the computing unit 121 may determine the UFR for the subject. Consider “s_a” as the first digital signal by the first signal converter 113 and “s_v” as the second digital signal by the second signal converter 119. Below equation 1 shows a Lambert-Beer’s relationship between s_a and s_v assuming the variation of the haemoglobin concentration across the dialyser 105 is small.
s_v=s_a e^(-a(?Hb?_a-?Hb?_v )d)………………………………………………………………..….…(1)
Where, a and d represents molar attenuation coefficient and optical path length, respectively. On taking terms up to linear approximation using Taylor series expansion yields equation 2.
s_v=s_a (1-a.d(?Hb?_a-?Hb?_v ))……………………………………………………….……(2)
Thus, the above relationship implies equation 3.
((s_a-s_v ))/s_a = a.d(?Hb?_a-?Hb?_v ), …………………………………………………………..……(3)
Further, the change in haemoglobin concentration(?Hb?_a-?Hb?_v ) is only possible by ultrafiltration process, which implies to be proportional to UFR that is expressed as equation 4 below.
(?Hb?_a-?Hb?_v )=c.UFR……………………………………………………………………..(4)
Hence,((s_a-s_v ))/s_a = a.d.c.UFR=k UFR…………………………………………………….(5)
where k=a.d.c
Defining index of UFR, I_UFR as equation 6 below.
I_UFR=k UFR……………………………………………………………………………….(6)
Further, the haemoglobin concentration ?Hb?_t is defined in terms of intravascular mass, m_(?Hb?_t ) and blood volume ?BV?_t at any time t as represented in equation 7.
?Hb?_t= m_(?Hb?_t )/?BV?_t ………………………………………………………………………………… (7)
Fig.2a illustrates an exemplary dialysis apparatus for providing personalised dialysis to subject in accordance with some embodiments of the present disclosure.

Fig.2a shows a dialysis apparatus 200 for providing personalised dialysis to the subject. The dialysis apparatus 200 comprises a dialysing sensing device 201, an extracorporeal blood circuitry 203, the dialyser 105, a dialysis fluid circuitry 205, an optical spectral electrolyte estimation device 207, a decision and control device 209 and the UFR determination device 101. Fig.2b shows an exemplary representation of dialysing sensing device in accordance with some embodiments of the present disclosure. As shown in the Fig.2b, the dialysing sensing device 201 includes a support structure 219 in which the subject is laid down during the dialysis. The support structure 219 comprises an arrangement to draw blood from the subject for removing excess fluid and to fed back the blood back to the subject. The dialysing sensing device 201 includes an Electrocardiography (ECG) acquisition unit 211 connected to the subject through one or more ECG electrodes for acquiring ECG signals of the subject, a Blood Pressure (BP) and Ballistocardiography (BCG) signal acquisition unit 213 connected to the subject for monitoring the BP of the subject, a Photoplethysmography (PPG) signal acquisition unit 215 connected to a PPG sensor attached to the subject for monitoring urea in blood of the subject, a weight acquisition unit 217 which includes one or more sensors connected to the support structure 219 for monitoring weight of the subject.
In an embodiment, the ECG acquisition unit 211 facilitates to acquire ECG signal of the subject through set leads 221 depending upon number of connected ECG electrode. Returning back to Fig.2a, the extracorporeal blood circuitry 203 is connected to the subject for drawing the blood sample from the subject for ultrafiltration and pushing the blood sample back to the subject. The dialysis fluid circuitry 205 is configured for preparing a dialysate solution and the dialyser 105 is connected to the dialysis fluid circuitry 205 for receiving the dialysate solution and the blood sample from the extracorporeal blood circuitry 203. The optical spectral electrolyte estimation device 207 estimates concentration of one or more electrolytes, such as, sodium ion and phosphate in the blood sample. The decision and control device 209 may receive inputs from the ECG acquisition unit 211, the BP and BCG signal acquisition unit 213, the PPG signal acquisition unit 215 and the weight acquisition unit 217 to assist in the dialysis. In an embodiment, real time body weight and BP of the subject may be estimated using electronic weight scale sensor which may be integrated to the support structure 219. Particularly, the support structure 219 may be attached with the BP and BCG signal acquisition unit 213 which may provide online BP measurement of BP and continuous or periodic weight measurement while undergoing dialysis. Further, a differential weight is computed using offline weight which may be stored before carrying out the dialysis. Thus, the net weight and the measured BP is fed to the decision and control device 209 for controlling ultrafiltration. In an embodiment, the decision and control device 209 may provide alarms to operators based on analysis.

In an embodiment, one or more morphological parameters of ECG wave (as explained in Fig.5a) may provide qualitative information for various alarming condition during the ultrafiltration. In an embodiment, combined ECG and BCG from the ECG acquisition unit 211 and the BP and BCG signal acquisition unit 213 may assist in determining and validating blood pressure apart from giving a continuous measurement. Further, identification of amount of urea in blood estimated using PPG signal may assist in continuing with ultrafiltration for fluid balance. In an embodiment, dry weight determination plays a crucial role. When dry weight is below a predefined threshold range, causes thirst, dry mouth, cramping, nausea, restlessness, cold extremities, rapid heartbeat and the like. Thus, the decision and control device 209 may provide decision to alarm and alert a medical assistance or may stop the dialysis process based on the inputs from the one or more devices.

Fig.3a illustrates a flowchart showing a method for computing volume of dialysate solution and of blood sample for dialysis in accordance with some embodiments of present disclosure.
FIG. 3a illustrates a method of computing volume of dialysate solution and of blood sample using an optical arrangement.
At block 301, the UFR determined by the UFR determination device 101 is obtained.
At block 303, the flow rate of the dialysate solution is set by the UFR determination device 101 in the dialyser as one of, less than or equal to the UFR determination for the subject.

At block 305, the speed of ultrafiltration pump (UFP) is configured more than speed of the UFR based on the set flow rate of the dialysate solution.

At block 307, the flow rate of the dialysate solution is set higher than flow rate of blood and lesser than the flow of the UFR. Typically, for example, the dialysate solution may be set 2 times of the flow rate of blood.

At block 309, the speed of a dialysate pump present is configured based on the set flow rate. The speed of the dialysate pump depends on the required flow rate. In an embodiment, values of dialysate flow rate ranges between 400mL/min to 800mL/min and value of blood flow rate for ultrafiltration is around 200ml/min, (practiced range is 200mL/min to 400mL/min). In an embodiment, a range of UF rate (UFR) is (100ML/min to 400mL/min) and may be at least 40mL/min. In an embodiment, several methods may be present to find dialysate speed in rpm for a flow rate. In one method, the dialysate speed is determined in rpm versus flow rate for specific tubing diameter and fluid. For instance, by forming truth table or relationship graph and setting the rpm based on flow rate required. The speed in rpm versus flow rate is performed offline for specific pumps, fluid, tubing dimension etc.

At block 311, the flow rate of blood sample is configured more than flow rate of blood in venous valve.

At block 313, the flow rate of blood sample is configured more than flow rate of blood in arterial valve.

At block 315, configuring speed of blood pump based on blood flow rate in arterial valve.
At block 317, the volume of dialysate solution is computed based on the flow rate of the dialyser, diameter of tubing and duration. In an embodiment, value of the diameter of tubing is 5mm.

At block 319, the volume of blood sample is computed based on the set flow rate of the blood, diameter of tubing and duration of flow.

Fig.3b illustrates a flowchart showing a method for reconfiguring speed of UFR pump in accordance with some embodiments of present disclosure.
Fig.3b shows a flowchart for reconfiguring speed of UFR pump. At block 321, the arterial blood flow is obtained.
At block 323, the arterial blood flow is obtained.
At block 325, the blood flow rate is set lesser than the arterial and venous blood flow by considering blood flow rate f_b=min?(f_a,f_v ).
At block 327, the dialysate flow rate is set less than the blood flow rate.
At block 329, the UFR is set lesser than and equal to dialysate flow rate. In an embodiment, the UFR may be at least 1.5.
At block 331, the rate of ultrafiltration pump speed is set greater than the UFR.
Fig.4 shows an exemplary representation of estimating urea concentration in the blood sample in accordance with some embodiments of present disclosure.

FIG.4 depicts an optical set up for estimating urea concentration. As shown, an optical setup includes a live blood flow across vein of the subject. The optical setup includes a LED light source 401 with a wavelength around 995nm (which is in the infrared range) and a photodiode detector 402 which are positioned across the vein one at a position before blood drawn to the dialyzer and the other after the blood feeding position from dialyzer to the vein. The LED light source 401 radiates light rays onto the vein. The photodiode detector 402 detects reflected light rays and produces a typical analog signal Basically, the analog signal produced may be proportional to both DC components corresponding to various tissues, bone tissue, venous and arteries blood components and AC components corresponding to blood urea nitrogen aviations, which is converted from the light rays into analog signal as shown at 405. At 407, the analog signal known as PPG waveform as shown in Fig.4 is converted to digital value. This may involve obtaining analog PPG waveform by having DC component removal by suitable high pass filter, suitable amplification and power frequency removal by suitable low pass filter. Further, digital PPG value as urea concentration in blood is determined from analog PPG waveform by suitable analog to digital conversion. At 409, a differential value is determined between digital values of the PPG waveform obtained between the photodiode detector 402 placed before and after blood is drawn and feed as shown in Fig. 4.
In an embodiment, urea concentration is proportional to magnitude of PSD of the digital PPG waveform upon suitable calibration. The concentration in the urea level may increases for subject having renal failure. The urea concentration is based one value of spectrum that is evaluated based on absorption near infrared spectroscopic technique. The value is suitably calibrated, and the urea concentration is estimated for providing to the decision and control device 209 of the dialysis apparatus 200. In an embodiment, the estimation of urea concentration is based on an estimation model. The estimation model at block 409 is a calibrated non-invasive PPG based urea estimator. In an embodiment, the process of calibration may involve either standard partial least squares regression or principal component regression method. While calibrating, consider a set of concentration of urea in blood having various levels which are measured using standard chemo metric methods that are practiced in clinical evaluation and a corresponding PPG value is obtained. Further, both the measured levels are used to estimate the model.
In an embodiment, allowable normal range of serum/plasma urea is 2.5 mmol/L-7.8 mmol/L. The dysuremea declaration is dependent upon the detected urea concentration which is below 2.5 mmol/L or above 7.8 mmol/L.
Fig.5a shows an exemplary flowchart detecting electrolytes imbalance conditions in accordance with some embodiments of present disclosure.

FIG.5a illustrates an online decision system for electrolytes imbalance.
At bock 501, an ECG wave is computed by the Electrocardiography (ECG) acquisition unit 211 as an ensemble average of a number of snapshots of ECG acquisitions.
At block 502, P wave, p(t), initial point and end points of p(t) as P_(i )&P_(e ) and peak ?P_M=max??(p(t)) is computed by considering ECG obtained at block 501.
At block 503, QRS wave q(t), initial and end point of q(t) as Q_(i ) and Q_(e )is identified. Further, width of wave q(t)=?Q_e-S?_(e )and peak as max?(q(t)) as R_Max and its position R_i is computed. Basically, QRS is complex wave since it is combined Q wave, R wave and S wave. It is linear combination of P, Q and R waves.
At block 504, S wave s(t)is identified and initial point and end points of s(t) as S_(i ) and S_(e ) are obtained based on block 509.
At block 505, wave T(t) is identified. Initial point and end points of T(t) as T_(i ) and T_(e ) and Peak T_Maxas max?(T(t))and position as T_i is obtained. Further, width of T(t) =T_e –T_(i ) is computed based on block 510
At block 506, U wave (u(t) ) is identified.
At block 507, check if P_(Max )=P_U. If true, then (1a) is decided which is Pericadities. Alternatively, the method moves to block 512.
At block 508, width(q(t)=R_M is verified. If, true, then decide (4b) (Hyper megnesimia). Otherwise, the method moves to block 511.
At block 509, ST interval = dist (S_(i . ) ? T?_i ) is computed.
At block 510, QT interval = distance between ( Q_(i . ) ? T?_s) is computed. QT interval prolongation is an indication of heart rhythm condition and chaotic heartbeat which cause fainting spell or seizure ultimately lead to fatal to health.
At block 511, T_Max=T_M , where T_M is pre-decided, is verified. If true, then it would be 1(d) (Ischemia/Hypomegnesmia) or 3(b) Hypercalcemia. Alternatively, the method moves to block 515.
At block 512, PR interval as distance between ( P_(i . ) ? R?_i) is computed.
At block 513, check if PR depressed is lower than the prior decide value. If yes, then decide as (4a) (Hypomegnesimia). Alternatively, the method moves to block 514.
At block 514, check both PR Interval=?PR?_U and 0=Slope(PR)= P_M. If yes, then decide (1a) ( Pericadities). Alternatively, the method moves to block 516.
At block 515, width of (q(t)) =Q_U is verified. If true, then decide (3a) Hypo calcimia. Alternatively, method moves to block 516.
At block 516, width of q(t))>1.2sec is verified. If true, then decide (4a) (Hypomegnesimia). Alternatively, method moves to block 504.
At block 517, QT interval >?QT?_U, where ?QT?_U is prior decided value is verified. If true, then decide (3a) (Hypo calcimia). Alternatively, the method moves to block 518.
At block 518, QT interval >?QT?_L is verified. If true, then decide (3b) (Hypercalcemia). Alternatively, the method moves to block 519.
At block 519, ST interval >?ST?_U, where ?ST?_U is predefined upper value, is verified. If yes, decide (2b) (Hyperkalemia). Alternatively, the method moves to block 521.
At block 520, ST segment depression with reference to baseline ECG is determined.
At block 521, check if ST depression is lesser than value M, which is again pre-calculated. If yes, then decide (1c) (Acute MI) and (4a) (Hypomegnesimia). Otherwise, the method moves to block 522.
At block 522, ST segment elevation with respect to baseline ECG is determined.
At block 523, check if ST elevation is greater than STu, where U is again predetermined. If true, then decide as (1d/4a) (Ischemia/Hypomegnesmia/ Hypomegnesimia). Alternatively, the method moves to block 514.
At block 524, peak of U wave as set as U_M is identified.
At block 525, U_M=T_M is verified. If true, then decide (2a) (Hypokalemia). Alternatively, the method moves to block 501 for repeating the process.
Fig.5b shows an exemplary representation of estimating concentration of one or more electrolytes in the blood sample in accordance with some embodiments of present disclosure. FIG. 5bshows an exemplary setup for estimating concentration of the one or more electrolytes in the blood sample. As shown a dialysate supplementary path 527 is present which is drawn from outlet extracorporeal blood tubing and is arranged between an optical set up 529 having a laser light source 531. The laser light source 531 excites light beams on the blood sample drawn from the blood flow tube 103 attached to the dialyser. Particularly, the light beams are made to fall on the dialysate supplementary path 527 and the optical setup 529. The optical set up 529 includes a fibre optics tube 533 which provides optical signals based on the light beams and a prism 535 which detects one or more spectrums based on the optical signals. Further, the setup includes a spectrograph detector 537 which estimates concentration of one or more electrolytes in the blood sample based on the one or more spectrums, considering blood flow rate and diameter of supplementary blood path as inputs.

Fig. 5c shows an exemplary representation of estimating concentration of electrolytes in dialysate sample in accordance with some embodiments of present disclosure. Fig.5c shows an optical set for online dialysis electrolyte estimation and analysis. The optical set comprises a dialysate supplementary path 539, which is drawn from outlet dialysis tubing and is arranged between an optical set up 529. The beams of the laser light source 531 are made to fall on supplementary dialysis fluid path 539 and optical setup 529. The optical set up 529 includes a fibre optics tube 533 which provides optical signals based on the light beams and a prism 535 which detects one or more spectrums based on the optical signals. Further, the setup includes a spectrograph detector 537 which estimates concentration of one or more electrolytes in the dialysate sample based on the one or more spectrums, based on dialysate flow rate and diameter of the supplementary dialysis fluid tubing.
Fig.6a and Fig.6b show exemplary representations of inter-dialytic ultrafiltration rate controller and intradialytic ultrafiltration rate controller respectively in accordance with some embodiments of present disclosure.

Fig.6a illustrates an exemplary representation for inter-dialytic ultrafiltration rate control, where the subject may undergo dialysis periodically as sessions. Particularly, block 601 includes an offline monitoring and estimation process, block 602 includes an online monitoring and estimation processes and block 603 includes decision and control processes.
At block 601, blood or serum nitrogen is estimated.
The block 602 includes processes of block 604, 605, 606, 607 and 608.
At block 604, body weight gain/loss is estimated. The body weight is obtained at any two intermediate instants using weight acquisition unit 217, which is arranged as shown in FIG.2b.
At block 605, red blood volume estimation is performed either as hyper-volumea or hypo -voloumea.

At block 606, real time estimation of Hct or hemoglobin data is performed.

At block 607, dysureamia detection process is performed (the setup is shown in Fig.4).
At block 608, dyselectroletima condition detection is performed.
The block 603 includes system for performing alarming and control system 609 to stop dialysis as indicated by few output at block 602. Further, block 603 includes decision signal to control the blood pump 610. Additionally, block 603 indicates signal for dialysate composition of various fluids for balancing process at block 611.
FIG. 6b describe exemplary representation for intradialytic ultrafiltration rate control. Particularly, at block 612 the ECG acquisition unit 211 is present for supplying one or more symptoms to block 613.
The block 613 is a real time ultrafiltration condition control signal generation process. The block 613 consists of block 615 for fluid electrolyte balance condition monitoring system, block 618 for blood volume estimation system, block 617 for hypotension detection system. Further, block 613includes block 616 for blood pressure monitoring system and block 619 for myocardial infarction symptoms detection system.
Block 614 is for decision and control process. The block 614 includes block 620 for dialysate composition for fluid balancing based on process 615, the block 621 for dialysis control or alarm system based on signal from block 616 and 617. Further, the block 614 includes a block 622 for reset of the ultrafiltration on signal condition from block 618 and a block 623 for dialysis control or alarm system based on signal given by block 619.
Fig.6c shows an exemplary representation of inter and intradialytic ultrafiltration rate controller in accordance with some embodiments of present disclosure.

Fig.6c represents combined representation of Fig.6a and Fig.6b. Particularly, block 625 is an offline monitoring and estimation processes which are carried out before session of dialysis to take the actual account of the conditions of the subject undergoing dialysis. The block 615 includes block 618 for serum urea nitrogen measurement process and block 629 for urea detection process. Block 626 represents an online control estimation process which includes block 630 for online body weight gain/loss estimation process, a block 631 for estimating blood volume either as hyper-volumea, nomal-volumea and hypo-volomea condition.
During the intra ultra-filtration process, if we consider total body weight obtained as,
? W?_TBW=W_TS+W_TF, ………………………………………………………………….(8)
where, W_TS and W_TF represents total solid weight and total fluid weight. During intra ultra-filtration process, W_TS remains invariant, but there would be definitely variation in W_TF . On denoting the total body fluid as,
W_TF (i)=W_ICF (i)+W_ISF (i)+W_PF (i)+W_RBC (i)+W_OF (i) ………………………..(9)
where, W_ICF ?,W?_ISF,W_PF,W_OF represents weights corresponding to intracellular, interstitial, plasma and other fluids, respectively.
Though the excess fluid is removed through blood vessel causing the shifts in the fluid from intracellular, interstitial and plasma compartment, the change in the fluid weight at (i+1)^th instant to (i)^th instant could be attributed to only plasma fluid compartment only.
??W?_TF (i)= ??W?_TF (i)-???W?_TF (i+1)=W?_PF (i)………………………………………… (10)
Additionally, during the intra ultra-filtration process, on considering equation (1), the change in total body weight is represented by equation 4.
??W?_TBW= W_PF (i)-W_PF (i+1)…………………………………. (11)
Now, expressing the plasma fluid weight W_PFas,
W_PF=m_PF×g=V_PF×d_PF , …………………………………………. (12)
Where m_PF,V_PF,d_PF and g denotes fluid mass, fluid volume, fluid density and gravity, respectively.
From equation (5), change in weight is proportional to change in m_PF, this results in change in V_PF.
In the case of hydrated dialysis patient, plasma consists of both pure plasma and also unwanted fluid. In an embodiment, any impure plasma concentration depends on amount of excess water and other unwanted mixture of fluid concentration.
Since, density is defined as ratio between mass of an element and the volume of the element.
Whereas, mass concentration C_i is defined as ratio of mass constituent m_i solvent to the volume of the mixture, V_PF.
Note here that the density of the mixture, d_PF is given by sum of the concentration of constituents of impure plasma, typically given by
d_PF=C_Plasma+C_RBC+C_OF +d_W …………………………………… (13)
Note from equation (13), density of plasma changes when certain amount of mass both other fluid and water is removed, which is given by ? ?m?_PF. This implies that weight of the dialysis patient is reduced by ??W?_PF in proportional to ? ?m?_PF, because gravity remains constant. Further, the reduction in weight is inversely proportional to volume of water removed.
Further, the block 626 includes a block 632 for real time HcT or hemoglobin data measuring and monitoring system and a block 633 for fluid electrolyte balance monitoring system and process. Further, block 627 is for decision and control that includes an alarm system 634, a blood pump speed controller 635 and block 636 for dialysate composition for fluid balancing process.
Fig.7 and Fig.8 show exemplary representations of inter-dialytic ultrafiltration rate controller and intradialytic ultrafiltration rate controller respectively in accordance with some embodiments of present disclosure. Table 1 illustrates typical value ranges for normal, hypo and hyper conditions parameters.
Solute Normal Dialysate concentration rang
(mmol/L) Dialysate concentration values for Hypo condition
(mmol/L) Dialysate concentration values for Hyper condition
(mmol/L)
Sodium 135 -145 < 135 >145
Potassium 1 - 4 <1 >4
Calcium 1:25 ?? 1:75 1.25-1.75 <1.25 >1.75
Chloride
98-124 <98 >124
Magnesium 0.5-0.75 <0.5 >0.75
Acetate/Citrate 2 - 4 <2 >4
Bicarbonate 30-38 <30 >38

Table 1
Fig.7 illustrates an offline or diagnostic time electrolyte safe range determination process, which includes block 701 for personalized ECG during diagnostic time.
At block 702 electrolyte (hypo or hyper) parameters are determined.
Block 703 composes of salient data base of personalized electrolytes, which is constrained by prescription by nephrologists at block 707. Further, Fig.7 illustrates an online or therapeutic electrolyte range determination process which includes block 704 for personalized ECG therapeutic duration, block 705 for online determination of electrolyte instant value. Further, the block 704 includes block 706 for generation of control signal based on comparison between current values with stored reference value for each electrolytes. The block 706 serves as resource input for block 708. FIG. 8 illustrates decision making process for personalized and prescription-based ultrafiltration rate control for dialysis to remove excess fluid in the blood.
Fig.9 illustrates a flowchart showing a method for determining personalised ultrafiltration rate for a subject during dialysis in accordance with some embodiments of the present disclosure.

As illustrated in Fig.9, the method 800 includes one or more blocks for determining personalised ultrafiltration rate for a subject during dialysis. The method 900 may be described in the general context of computer executable instructions. Generally, computer executable instructions can include routines, programs, objects, components, data structures, procedures, modules, and functions, which perform particular functions or implement particular abstract data types.

The order in which the method 900 is described is not intended to be construed as a limitation, and any number of the described method blocks can be combined in any order to implement the method. Additionally, individual blocks may be deleted from the methods without departing from the scope of the subject matter described herein. Furthermore, the method can be implemented in any suitable hardware, software, firmware, or combination thereof.

At block 901, light rays are projected to the blood sample flowing through the blood flow tube 103 by the first LED source 109 into the dialyser 105 of the dialysis apparatus 200.
At block 903, the first set of transmitted light rays are received by the first photodiode sensor 111 based on the light rays projected from the first LED source 109.

At block 905, the light rays are projected to the blood sample flowing through the blood flow tube 103 by the second LED source115 out of the dialyser 105.

At block 907, the second set of transmitted light rays are received by the second photodiode sensor 117 based on the light rays projected from the second LED source 115.

At block 909, the first set of signals and the second set of signals indicative of haemoglobin concentration in the blood sample are detected by the first photodiode sensor 111 and the second photodiode sensor 117 based on the first set of transmitted light rays and the second set of transmitted light rays, respectively.

At block 911, the variations in haemoglobin concentration of the blood sample are identified by the computing unit 121 based on the first set of signals and the second set of signals.

At block 913, the ultrafiltration rate for the subject is determined by the computing unit 121 based on the identified variations.

The terms “an embodiment”, “embodiment”, “embodiments”, “the embodiment”, “the embodiments”, “one or more embodiments”, “some embodiments”, and “one embodiment” mean “one or more (but not all) embodiments of the invention(s)” unless expressly specified otherwise.

The terms “including”, “comprising”, “having” and variations thereof mean “including but not limited to”, unless expressly specified otherwise.

The enumerated listing of items does not imply that any or all of the items are mutually exclusive, unless expressly specified otherwise.

The terms “a”, “an” and “the” mean “one or more”, unless expressly specified otherwise.

A description of an embodiment with several components in communication with each other does not imply that all such components are required. On the contrary, a variety of optional components are described to illustrate the wide variety of possible embodiments of the invention.

When a single device or article is described herein, it will be readily apparent that more than one device/article (whether or not they cooperate) may be used in place of a single device/article. Similarly, where more than one device or article is described herein (whether or not they cooperate), it will be readily apparent that a single device/article may be used in place of the more than one device or article or a different number of devices/articles may be used instead of the shown number of devices or programs. The functionality and/or the features of a device may be alternatively embodied by one or more other devices which are not explicitly described as having such functionality/features. Thus, other embodiments of the invention need not include the device itself.

The illustrated operations of Fig.9 show certain events occurring in a certain order. In alternative embodiments, certain operations may be performed in a different order, modified or removed. Moreover, steps may be added to the above described logic and still conform to the described embodiments. Further, operations described herein may occur sequentially or certain operations may be processed in parallel. Yet further, operations may be performed by a single processing unit or by distributed processing units.

Finally, the language used in the specification has been principally selected for readability and instructional purposes, and it may not have been selected to delineate or circumscribe the inventive subject matter. It is therefore intended that the scope of the invention be limited not by this detailed description, but rather by any claims that issue on an application based here on. Accordingly, the disclosure of the embodiments of the invention is intended to be illustrative, but not limiting, of the scope of the invention, which is set forth in the following claims.

While various aspects and embodiments have been disclosed herein, other aspects and embodiments will be apparent to those skilled in the art. The various aspects and embodiments disclosed herein are for purposes of illustration and are not intended to be limiting, with the true scope and spirit being indicated by the following claims.

REFERRAL NUMERALS:

Reference number Description
100 Environment
101 Ultrafiltration rate determination device
103 Blood flow tube
105 Dialyser
107 Blood sample
109 First LED source
111 First photodiode sensor
113 First signal converter
115 Second LED source
117 Second photodiode sensor
119 Second signal converter
121 Computing unit
200 Dialysis apparatus
201 Dialysing sensing device
203 Extracorporeal blood circuitry
205 Dialysis fluid circuitry
207 Optical spectral electrolyte estimation device
209 Decision and control device
211 ECG acquisition unit
213 BP and BCG signal acquisition unit
215 PPG signal acquisition unit
217 Weight acquisition unit
401 LED light source
403 Photodiode detector
405 Analog signal
527 Dialysate supplementary path
529 Optical set up
531 laser light source
533 Fibre optics tube
535 Prism
537 Spectrograph detector