Sensing of Surface Texture using Smart Glove for Post Stroke Rehabilitation

Post-stroke patients need to be rehabilitated in order to gain partly or fully some of the motor facilities that seem to have ceased to function effectively. According to the research, post-stroke deficits in the human ability to palpate and comprehend surface features is the major difficulty a stroke survivor may experience; often they cause harm or accidentally destroy objects due to an incorrect manner of holding them. This research offers a new strategy with the aid of wearable haptic interface in the form of a smart glove that employs an ESP32 microcontroller and force sensors to identify surface texture. Using pattern recognition, we can effectively distinguish between a rough and a smooth surface to adapt to the pressure required to hold any object. This innovation apart from improving safety also gives the patient feedback in the process of rehabilitation. The use of machine learning in particular proves to be more preferable when it comes to texture recognition preventing shortcomings observed in other senor-based approaches.