Patient Healthcare System

Raw biomedical signals are rich with useful information and used in industrial applications such as entertainment, medical, artificial robotic arms and controlling purposes. The electric signal produced during muscle activation known as the EMG signal, is produced from small electrical currents gene

Project Title

Patient Healthcare System

Project Area of Specialization

Biomedical Engineering

Project Summary

Raw biomedical signals are rich with useful information and used in industrial applications such as entertainment, medical, artificial robotic arms and controlling purposes. The electric signal produced during muscle activation known as the EMG signal, is produced from small electrical currents generated by the exchange of ions across the muscle membranes. These signals can be detected with the help of surface electrodes.

Nowadays EMG signals are used for biomedical applications, robotics arms, ergonomic design, medical research, sports sciences, and evolvable hardware (EHW) chips evaluations. EMG signals could be used to control existing, commercially available multifunctional myo-electric prostheses. Moreover, it also provides control options to amputees, who are not able to use conventional control system. EMG signals based control systems are extremely valuable for handicapped people as speech recognition based control systems. Recently, various efforts in human computer interaction (HCI) has been developed using user friendly interfaces such as voice, gestures and vision recognition. The most challenging approaches in HCI are to interface computers with biomedical signals such as Electroencephalogram (EEG), Electrocardiogram (ECG), and Electromyogram (EMG). EMG Signal generated by arm muscles is a raw biomedical signal that contains different noises such as instability of signals, motion artifacts, ambient, cross talk, transducer, equipment noise and the interaction of different tissues so preprocessing techniques are used to remove these noises. The amplitude of surface EMG signal lies within the range of 1-10mV which is slightly higher than amplitude of EEG signal. The range of frequency contents lies between 0Hz to 450Hz, and signal’s dominant range is from 50Hz to 150Hz. The dominant region for ambient noise is 48Hz to 52Hz. Due to motion artifacts frequency range 0Hz to 20Hz is unstable, there are two main reasons of motion artifacts: first one is movements of connecting wires between surface electrodes and amplifier circuit and the second is instability of electrodes on the skin.

Project Objectives

1. To provide a control options to those individuals, who are not capable to use conventional control systems. Electromyogram (EMG signal) based control systems are extremely valuable for handicapped people as gesture recognition based control system.  
2. EMG signals could be used to control existing, commercially available multifunctional myo-electric prostheses.

Project Implementation Method

In this project first of all signal is acquired through arm muscles by surface electrodes. The acquired signal is filtered to remove all the noises. Two filters are used bandpass and bandstop filters. The filtered signal is then segmented in time domain so that it is suitable for feature extraction. Different features such as average rectified value (ARV), root mean square (RMS), skewness, kurtosis and energy are extracted from segmented EMG signal. Based on these features system classified the signal for different gestures. After classification user will be able to convey the messages to caretaker through GSM using user’s active muscle (EMG) signal instead of using the remote control unit.

Benefits of the Project

1. Control options to those individuals, who are not capable to use conventional control systems. Electromyogram (EMG signal) based control systems are extremely valuable for handicapped people as gesture recognition based control system will be provided.  
2. EMG signals could be used to control existing, commercially available multifunctional myo-electric prostheses.
3. User friendly, it can be used for different applications depending on user’s choice like video games, toys for special handicapped children etc.

Technical Details of Final Deliverable

In this project EMG signal is acquired by using the surface electrodes which are placed on arm muscles. EMG Signal acquired through arm muscles is a raw biomedical signal that contains different noises such as instability of signals, motion artifacts, ambient, cross talk, transducer, equipment noise and the interaction of different tissues so preprocessing techniques are used to remove these noises. EMG Signal passed through an instrumentation amplifier (INA 128) to remove common mode noise and to amplify the signal. A Driven Right Leg (DRL) circuit is used to remove the common mode interference. Bandpass filter of 20Hz to 450Hz is used because the signal is unstable from 0Hz to 20Hz and a bandstop filter of 48Hz to 52Hz is used to remove ambient noise which is dominant in this range. Then features extraction and classification is done.

Final Deliverable of the Project

HW/SW integrated system

Core Industry

Health

Other Industries

Medical

Core Technology

Others

Other Technologies

Sustainable Development Goals

Good Health and Well-Being for People

Required Resources

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