Published 2025-05-01
Keywords
- Gesture-based communication, Flex sensors, ESP32 microcontroller, Wearable communication system, Blynk IoT platform
Abstract
Effective communication remains a significant challenge for individuals with paralysis or severe physical disabilities. Existing communication aids such as sign language and speech-generating devices often face limitations related to complexity, cost, and the requirement of prior training. This research introduces a novel “IoT and cloud enabled Motion Communication and ML Assisted Recovery system for Paralytics,” a wearable, gesture-based communication system integrated with Internet of Things (IoT) technology. The device employs a glove embedded with five flex sensors to detect finger movements and translate these into binary signals corresponding to predefined messages. An ESP32 microcontroller processes these signals and transmits messages via Wi-Fi using the Blynk IoT platform to caregivers’ mobile applications in real time.