Biosignal acquisition and interfacing technique for post stroke rehabilitation

This thesis presented a wireless monitoring system which consist of data logging function for hand movement related both to sportsman and patient. The system which comprised of the application of gyroscope and accelerometer sensor was tested on healthy normal subject for the initial proof of concept. The subject was needed to wear a set of sensors over the wrist while performing few basic arm movements. The study focused on designing, developing and simulating the experimental results. The recorded result can be used for the purpose of postprocessing and progressive status tracking. The data was saved into a microSD card for further analysing purposes. The system was then used for different application with the addition of tilt sensors. The subject was required to wear a set of sensors over the palm with the basic arm movements during the experiment. The experiment demonstrated the capabilities of the sensors to produce the extended information and also the Android applications in responding to the hand movement activities in real time. The results obtained from the experiments were presented in various graphical representations which showed the stability of the system in producing the consistence output. It offered more information with the ability to improve the training quality and also monitoring the progress of the sportsmen and post-stroke patients. Lastly, the interactive output developed would enable the users to keep track on their performance level and thus eventually, motivates them to continue successfully the training or therapy session

Locomotors Rehabilitation System via Gait Analysis with Load cell, Gyroscope and Accelerometer Sensor

Locomotors Rehabilitation System (LRS) has a potential used with the advancement in electronic and computer. It requires sensors for a locomotion measurement and units to communicate between patients and the doctors. These promote a flexible and economical solution to a Gait analysis by develops units to differentiate the abnormal and normal patient different walking pattern. The LRS consist of a PIC microcontroller, RF transceiver, analogue multiplexer plus sensors for the compressive force, acceleration and angular velocity measurement. Later, these measurements are sent to the computer for further human locomotion analysis. The data transmission is optimized up to 250 meters line of sight with ±3 g acceleration, tilt angle at ± 0.1 ° and ≤ 150 Kg bodyweight measurement. The LRS is expected to offer more information than the Gait analysis and also the ability to improve the clinical and rehabilitation applications