Tactile signatures and hand motion intent recognition for wearable assistive devices

Within the field of robotics and autonomous systems where there is a human in the loop, intent recognition plays an important role. This is especially true for wearable assistive devices used for rehabilitation, particularly post-stroke recovery. This paper reports results on the use of tactile patterns to detect weak muscle contractions in the forearm while at the same time associating these patterns with the muscle synergies during different grips. To investigate this concept, a series of experiments with healthy participants were carried out using a tactile arm brace (TAB) on the forearm while performing four different types of grip. The expected force patterns were established by analysing the muscle synergies of the four grip types and the forearm physiology. The results showed that the tactile signatures of the forearm recorded on the TAB align with the anticipated force patterns. Furthermore, a linear separability of the data across all four grip types was identified. Using the TAB data, machine learning algorithms achieved a 99% classification accuracy. The TAB results were highly comparable to a similar commercial intent recognition system based on a surface electromyography (sEMG) sensing

Braille Display Systems for Blind People with Haptic Belt

This manuscript addresses the development of a microcontroller-based braille display system. Recently, tactile display devices use technologies such as electric motors, piezoelectric, and solenoids as actuators. Nevertheless, the device is seeming to be bulky, inflexible, and far from soft actuation. Thus, the project in this manuscript portrays the development of a new design by using Micro servomotors and embedded soft- computing algorithms. The system consists of a haptic belt and a sensing unit. The sensing part of a Braille cell is designed to be wearable on arm. The methodology to reach the outcomes involving the ATmega328P microcontroller in the Arduino board, Tower Pro SG51R micro servo, and the LV-MaxSonar-EZ1 ultrasonic sensor. These apparatuses are lumped in a Braille Display System with a Haptic Belt. The performance and functionality of the system are evaluated based on its ability to detect obstacles from four different locations by means of ultra- sonic sensors. The sensors actuate the servomotors to notice the blind. The system works well around 0.5 meters radius. The boundedness of the system radius is acceptable to secure ample time for the scanning process. The responses of the sensors upon various obstacles are presented in this manuscript with a thorough analysis

Braille display systems for blind people with haptic belt

This manuscript addresses the development of a microcontroller-based braille display system. Recently, tactile display devices use technologies such as electric motors, piezoelectric, and solenoids as actuators. Nevertheless, the device is seeming to be bulky, inflexible, and far from soft actuation. Thus, the project in this manuscript portrays the development of a new design by using Micro servomotors and embedded soft-computing algorithms. The system consists of a haptic belt and a sensing unit. The sensing part of a Braille cell is designed to be wearable on arm. The methodology to reach the outcomes involving the ATmega328P microcontroller in the Arduino board, Tower Pro SG51R micro servo, and the LV-MaxSonar-EZ1 ultrasonic sensor. These apparatuses are lumped in a Braille Display System with a Haptic Belt. The performance and functionality of the system are evaluated based on its ability to detect obstacles from four different locations by means of ultra-sonic sensors. The sensors actuate the servomotors to notice the blind. The system works well around 0.5 meters radius. The boundedness of the system radius is acceptable to secure ample time for the scanning process. The responses of the sensors upon various obstacles are presented in this manuscript with a thorough analysis