Researchers at the Indian Institute of Technology (IIT), Delhi have developed a scalable, wearable pressure sensor, offering a cost-effective alternative to expensive footwear modifications, surgeries, and posture-correcting accessories. The new sensor is based on a nanocomposite material that has a special combination of light-sensitive polymer and piezoelectric nanoparticles. This material has the advantage of easy array design for pixelated sensing over large areas, simple process flow, and low-cost implementation for human movement monitoring and injury rehabilitation.
In a study published in the journal Nano Energy, the researchers demonstrated the sensor's remarkable flexibility, effectively turning it into a versatile sensor array that can comfortably fit various insole sizes or be conveniently attached to the palm or other body regions where localized pressure detection is valuable. By incorporating a dual transduction nanocomposite, the sensor can simultaneously capture mechanical strain and contact force/pressure, seamlessly integrating into modern Machine Learning algorithms by delivering enhanced feature components.
Lead researcher Dr Dhiman Mallick, an assistant professor in the Electrical Engineering Department at IIT Delhi, emphasised the promising prospects that arise from the integration of sensors and Machine Learning, revolutionising cutting-edge applications in healthcare, sports science, and defense.
"The integration of sensors and Machine Learning leads to the invention of intelligent sensors for cutting-edge technologies in fields like healthcare, sports science, and defense. During the numerous tests conducted in our laboratory, we found that the proposed sensor can potentially help detect foot problems in both adults and children by analyzing the pressure variation on the back end of the foot and converting it into electrical output. Given that abnormal hindfoot pressure distribution can lead to problems in knee joints, hips, and even spine-related injuries, understanding and correcting it is of great importance," said Dr Dhiman Mallick.
The sensor's output is analysed using conventional Machine Learning models, allowing clinicians to compare pressure patterns with predefined norms for a typical individual, thereby determining the type of deformity present. These pressure patterns can guide medical practitioners and specialists in designing custom insoles to mitigate foot deformities, redistributing pressure to correct abnormal distributions. In essence, this innovative sensor represents an accessible, economical solution to costly footwear modifications, surgeries, and posture correction devices.
Furthermore, the sensor holds significant potential in deciphering various human activities, such as walking or running, through its ability to detect pressure changes in the hindfoot. This innovation can be highly advantageous in smart healthcare systems, where parameters like activity patterns, exercise intensity, and step counts are vital for comprehensive health analysis in individuals with conditions such as diabetes and obesity.
Additionally, the sensor may contribute to elderly fall detection, especially in patients with Parkinson's disease or those with disabilities, and it can support injury rehabilitation.