Pukar Maharjan

Voice communication is the most effective and forthright approach of connecting individuals that we use to share our feelings, emotions, opinions, ideas, information, and so on. However, people with speech disorder and hearing disorder use sign language using hand gestures for communication which might not be easily understandable for everyone. Sensing and converting those hand gestures by using self-powered sensors is the main goal of this project. 

Drawn inspiration from the highly sensitive human skin dermis-epidermis interlocked haptic performance, a highly sensitive and facile fabricated self-powered triboelectric flex sensor (STFS) is developed which can efficiently detect the finger bending motion and monitor the hand gestures.

Password-based authentication system has been the most popular method for authenticating users in computing devices and system access, where keyboards are used to input PINs, tokens, or passwords. However, it becomes more fragile for weak passwords and prone to numerous attacks such as dictionary attacks, guessing attacks, and shoulder surfing attacks.

In this work, we developed a keystroke dynamics based hybrid self-powered sensors for biometric authentication and identification integrated with AI. Keystroke dynamics offer behavioral and contextual information that can distinguish and authorize the individuals based on their typing rhythms. Our system achieves an accuracy of 99% and offers a promising hybrid security layer against password vulnerability.

With the increase in portable smart electronic devices, WSN, and continuously running health-care monitoring sensors, energy deficiency has been a big challenge. As a result, more efforts have been focused on developing energy harvesting devices that can replace the conventional batteries to realize a self-powered system by scavenging energy from ambient sources such as human biomechanical energy.

Herein, a universal self-chargeable power module is designed and developed, that can efficiently harvest energy from human motion, ocean water waves, and automobile vibrations. It is a compactly designed device including a power management circuit, a battery charging circuit, built-in rechargeable storage, and a USB-C outlet, providing a direct current power of maximum 34.11 mW.

Converting biomechanical energy wasted during human locomotion into electrical energy is a promising avenue for powering body-worn devices such as smartwatches, fitness bands, health monitoring sensors such as CGM, pulse sensor, etc. However, most of the conventional energy harvesting devices were not actually wearable and challenging for real time practical applications. 

In this project, we designed a novel curve-shaped wearable hybridized electromagnetic-triboelectric nanogenerator, operating as a fully-enclosed light-weight low-frequency energy harvester, driven by human motion. The device can power a commercial wrist watch continuously for 7 minutes from just 5 seconds of arm swinging during locomotion.