Shape conformable high spatial resolution tactile bracelet for detecting hand and wrist activity

Koiva R, Riedenklau E, Viegas C, Castellini C (2015)


Publication Type: Conference contribution

Publication year: 2015

Journal

Publisher: IEEE Computer Society

Book Volume: 2015-September

Pages Range: 157-162

Conference Proceedings Title: IEEE International Conference on Rehabilitation Robotics

Event location: Singapore SG

ISBN: 9781479918072

DOI: 10.1109/ICORR.2015.7281192

Abstract

We present a novel sensory device that can non-invasively capture the muscle activations in the lower arm in unprecedented detail. The primary motivation for building the sensor was to have a new input channel to control modern state-of-The-art multi-degree-of-freedom prosthetic hands, but many interesting use cases have arisen such as its use as an input device in the areas of manual intelligence research, computer gaming and immersive virtual reality environments. The modular compact tactile sensor bracelet has up to 320 highly sensitive sensor elements and measures the bulgings of muscles around the full circumference of the arm. In a preliminary experiment described in this paper, we trained a linear regression model to learn the mapping between the sensor values and flexion of three fingers plus two degrees of freedom of the wrist. The results show that the measured high dimensional force pattern corresponds to targeted single-digit activity. The soft surface of the sensor and the flexible links between the single modules make the bracelet comfortable to wear and conformable to various arm and residual limb shapes.

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How to cite

APA:

Koiva, R., Riedenklau, E., Viegas, C., & Castellini, C. (2015). Shape conformable high spatial resolution tactile bracelet for detecting hand and wrist activity. In David Braun, Haoyong Yu, Domenico Campolo (Eds.), IEEE International Conference on Rehabilitation Robotics (pp. 157-162). Singapore, SG: IEEE Computer Society.

MLA:

Koiva, Risto, et al. "Shape conformable high spatial resolution tactile bracelet for detecting hand and wrist activity." Proceedings of the 14th IEEE/RAS-EMBS International Conference on Rehabilitation Robotics, ICORR 2015, Singapore Ed. David Braun, Haoyong Yu, Domenico Campolo, IEEE Computer Society, 2015. 157-162.

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