A variety of exercises are typically prescribed as part of physiotherapy to restore physical strength in victims of stroke or patients of arthritis experiencing muscle weakness like repetitive movement of hands in picking up an object from one point to another. Researchers at the International Institute of Information Technology-Hyderabad (IIIT-H) PATRIoT lab have come out with a new-age, low-cost pressure sensor to analyse and recognise such activity unobtrusively.
Flexible electronics or developing thin, bendable and stretchable circuits for ‘smart’ applications is one of the fortes of this group. “In this case, apart from the typical smart properties of sensors, we also wanted to cover a large area and try to map the pressure distribution in the entire area,” says Aftab Hussain, principal investigator.
Their experiment canvas for the required physical rehabilitation exercises was a sensory mat containing designated areas for placing weights. With conductive foam as the main ingredient, this low-cost paper-based 4X4 pressure sensor matrix was fabricated with a layer of paper each on top and the bottom, sandwiching copper electrodes.
Each time the foam is pressed by a patient, with the pressure application there is a reduction in resistance that can be detected through an external circuit. “We look if the value of resistance has changed and if it has, then we try to interpret how much pressure has been applied and where,” explains Mr Hussain.
Researchers trained a machine learning model to detect position of loads for various resistances. “Neural networks not only help in determining if the load was placed in the correct position but it can also learn from the responses of a person over a period of time,” says Anis Fatema, primary author of the study titled ‘A low-cost pressure sensor matrix for activity monitoring in stroke patients using artificial intelligence’, which was published in IEEE Sensors Journal.
The new device has the ability to quantify a physiotherapy session. “In addition to tracking progress of patients in terms of accuracy of where they are placing the load, one can also monitor time taken to place the load so that we can get both speed and accuracy of load positioning,” says Mr Hussain.
While the product, which uses a very thin-film fabrication technique, currently costs less than ₹1,000 a piece, the team is in the process of reducing the cost further. “We are checking if the conductive foam that made the sensor pixels possible can be made via synthetic organic chemistry. It will further reduce the costs, tweak the properties of foam to better suit our applications and make them more reliable,” he adds.
