DESC:Electrocardiography (ECG) is the recording of electrical activity of the heart by means of electrodes. It is used to measure heart’s electrical conduction system.
The device designed by us for measuring and analyzing ECG signals received from the body comes with three ECG electrodes. An user using the device has the option to perform ECG operations by placing three fingers on the respective electrodes attached to the device for instantaneous ECG measurement, or place wired ECG electrodes from our AMI Chest ECG/EEG unit on his/her left, right arm and left leg for continuous ECG monitoring.

ECG Signal Processing:
The signals received from the ECG electrodes are low pass filtered, amplified and then sampled by a controller to record the ECG signal. The received ECG signal is then processed to detect and interpret various ECG related parameters for detailed diagnosis of the heart functionality.

The algorithm involved processes the raw input ECG signal and correctly identifies and annotates the exact position of the P,Q,R,S,T complexes, it also gives an approximation of the onset and offset of the P,R and T waveforms. The method followed is as described here:

The input raw signal is first filtered digitally by means of a band pass filters (ECGBPF) to attenuate the noise components of the signal. This improves the signal to noise ratio and helps us to use lower thresholds than that would otherwise have been used had we not been filtering the signal. The ECGBPF signal is then differentiated to obtain an information of the slope of the QRS complex (ECGDIF), which is further squared (ECGSQR) with the intention to intensify the slope of the frequency response of the derivative. The ECGSQR signal is then moving window integrated to produce a signal (ECGINTE) which has information of both the slope and width of the QRS complex.

As the R of the QRS complex get detected, the algorithm searches for the nearest peak positions i.e. zero-crossings before and after the R point in the ECGDER .
According to the polarity and relative value of these peaks, we decide whether the peak belong to the Q or S wave. The points after being identified as valid, are subsequently marked as Q and S positions in the wave.
Once the Q, R and S wave positions are correctly identified, the P and T wave peaks are searched for. These waves having low frequency components more than the QRS complex, the ECGDER signal is again low pass filtered (ECGDERLF) to remove further noise. A 155ms window starting after previous Q wave and 255ms before R wave is chosen to be the possible location of the P wave. The maximum and minimum positions of the window are searched for in this window. If the detected values are greater than 2% of the maximum slope of the QRS complex, we assume that the valid P wave is present in the signal, else P wave cannot be located. The zero crossing between the detected maximum and minimum points is the exact position of a possible P wave.
On successful detection and mapping of the P, Q, R, S and T timestamps positions. We calculate the RR intervals, i.e. the interval between successive Rs. Since all normal beats not generated by sinus node depolarization have been eliminated by our previous steps of band pass filters, we call the RR interval as NN interval to emphasize on the fact that these processed beats are normal beats.
Heart Rate Variability Analysis
The detected timestamps of the P, Q, R, S, and T waveforms are further used to calculate the Heart Rate Variability of the ECG signal.
There are two types of Heart Rate Variability (HRV) analysis namely the Time Domain Analysis and Frequency Domain Analysis .All analysis for Heart Rate Variability are processed taking into consideration a fixed interval of 24Hours.
Time Domain Analysis (TDA):
The TDA employs the usage of few Time Domain Measures. They are:
a) AVNN: It is calculated by taking the mean of the NN intervals in milliseconds.
b) SDNN: It is calculated by calculating the Standard Deviation of N-N intervals in milliseconds. (Total HRV duration). The SDNN is the square root of the variance and since variance is mathematically equivalent to power spectral analysis, it reflects all cyclic components of variability in the recorded NN interval. The longer the record time the higher is the SDNN, so as a measure to keep a standard the SDNN is calculated for a record of 24 hours.
c) SDANN: This is the Standard Deviation of 5min mean values of NN interval in milliseconds.
d) SDNNIDX: It is the mean of the Standard Deviation of NNs in 5 min interval of a 24hour ECG recording in milliseconds.
e) rMSSD: In this we calculate the square root of the mean squared differences of successive NN intervals in milliseconds.
f) pNN50: It is calculated as the percentage of successive RRs that differ by more than 50ms.

Frequency Domain Analysis:

The Frequency Domain Analysis uses the following parameters

a) TOTPWR: This is calculated by calculating the total spectral power of all NN intervals up to 0.04Hz. This is calculated in milliseconds2.
b) ULF: This is calculated by calculating the total spectral power of all NN intervals up to 0.003Hz. This is calculated in milliseconds2.
c) VLF: This is calculated by calculating the total spectral power of all NN intervals between 0.003Hz and 0.04Hz. This is calculated in milliseconds2.
d) LF: This is calculated by calculating the total spectral power of all NN intervals between 0.04Hz and 0.15Hz. This is calculated in milliseconds2.
e) HF: This is calculated by calculating the total spectral power of all NN intervals between 0.15Hz to 04Hz. This is calculated in milliseconds2.
f) LF/HF: This is the ratio of low frequency power/ high frequency power.

The details about the interpretation for these HRV parameters is provided in the document “HRV Parameters and its Implementation”

The algorithm was tested using 40 different waveforms generated from Fluke Prosim 8 simulator using various combinations of amplitude and heart rate. The RR interval series for each of the waves were generated and the corresponding Standard Deviation was calculated for each of the waves followed by the calculation of relative standard deviation (percentage). For each of the waves the calculated relative standard deviation was within 1% – 2%.

,CLAIMS:A method of wearable device to determine continuous ECG /EEG measurement
b. A Method to determine the results in real time in smartphones Via Bluetooth technology
c. This device is the smallest ECG/EEG measurement tracker