1. Embedded Electrotactile Feedback System for Hand Prostheses using Matrix Electrode and Electronic Skin
- Author
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Moustafa Saleh, Yahya Abbass, Maurizio Valle, and Strahinja Dosen
- Subjects
Male ,Bionics ,prosthetic hand ,Computer science ,Interface (computing) ,Biomedical Engineering ,Electronic skin ,Artificial Limbs ,Feedback ,Wearable Electronic Devices ,Feedback, Sensory ,medicine ,Humans ,Computer vision ,Electrical and Electronic Engineering ,Electrodes ,Sensory feedback system ,business.industry ,Bandwidth (signal processing) ,electronic skin ,Index finger ,Hand ,electrotactile stimulation ,tactile sensors ,medicine.anatomical_structure ,Sensory substitution ,Touch ,Interfacing ,Female ,Artificial intelligence ,business ,Tactile sensor - Abstract
As the technology moves towards more human-like bionic limbs, it is necessary to develop a feedback system that provides active touch feedback to a user of a prosthetic hand. Most of the contemporary sensory substitution methods comprise simple position and force sensors combined with few discrete stimulation units, and hence they are characterized with a limited amount of information that can be transmitted by the feedback. The present study describes a novel system for tactile feedback integrating advanced multipoint sensing (electronic skin) and stimulation (matrix electrodes). The system comprises a flexible sensing array (16 sensors) integrated on the index finger of a Michelangelo prosthetic hand mockup, embedded interface electronics and multichannel stimulator connected to a flexible matrix electrode (24 pads). The developed system conveys contact information (binary detections) to the user. To demonstrate the feasibility, the system was tested in six able-bodied subjects who were asked to recognize static patterns (contact position) with two different spatial resolutions and dynamic movement patterns (i.e., sliding along and/or across the finger) presented on the electronic skin. The experiments demonstrated that the system successfully translated the mechanical interaction into electrotactile profiles, which the subjects could recognize with good performance. The success rates (mean pm standard deviation) for the static patterns were 91 pm 4% and 58 pm 10% for low and high spatial resolution, respectively, while the success rate for sliding touch was 94 pm 4%. These results demonstrate that the developed system is an important step towards a new generation of tactile feedback interfaces that can provide high-bandwidth connection between the user and his/her bionic limb. Such systems would allow mimicking spatially distributed natural feedback, thereby facilitating the control and embodiment of the artificial device into the user body scheme.
- Published
- 2021