Online Bimanual Manipulation Using Surface Electromyography and Incremental Learning

Strazzulla I, Nowak M, Controzzi M, Cipriani C, Castellini C (2017)

Publication Type: Journal article

Publication year: 2017

Journal

IEEE Transactions on Neural Systems and Rehabilitation Engineering Institute of Electrical and Electronics Engineers (IEEE)

Book Volume: 25

Pages Range: 227-234

Article Number: 7460959

Journal Issue: 3

DOI: 10.1109/TNSRE.2016.2554884

Abstract

The paradigm of simultaneous and proportional myocontrol of hand prostheses is gaining momentum in the rehabilitation robotics community. As opposed to the traditional surface electromyography classification schema, in simultaneous and proportional control the desired force/torque at each degree of freedom of the hand/wrist is predicted in real-time, giving to the individual a more natural experience, reducing the cognitive effort and improving his dexterity in daily-life activities. In this study we apply such an approach in a realistic manipulation scenario, using 10 non-linear incremental regression machines to predict the desired torques for each motor of two robotic hands. The prediction is enforced using two sets of surface electromyography electrodes and an incremental, non-linear machine learning technique called Incremental Ridge Regression with Random Fourier Features. Nine able-bodied subjects were engaged in a functional test with the aim to evaluate the performance of the system. The robotic hands were mounted on two hand/wrist orthopedic splints worn by healthy subjects and controlled online. An average completion rate of more than 95% was achieved in single-handed tasks and 84% in bimanual tasks. On average, 5 min of retraining were necessary on a total session duration of about 1 h and 40 min. This work sets a beginning in the study of bimanual manipulation with prostheses and will be carried on through experiments in unilateral and bilateral upper limb amputees thus increasing its scientific value.

Authors with CRIS profile

Claudio Castellini

Involved external institutions

Università degli Studi di Ferrara IT Italy (IT) Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR) / German Aerospace Center DE Germany (DE)

How to cite

APA:

Strazzulla, I., Nowak, M., Controzzi, M., Cipriani, C., & Castellini, C. (2017). Online Bimanual Manipulation Using Surface Electromyography and Incremental Learning. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 25(3), 227-234. https://dx.doi.org/10.1109/TNSRE.2016.2554884

MLA:

Strazzulla, Ilaria, et al. "Online Bimanual Manipulation Using Surface Electromyography and Incremental Learning." IEEE Transactions on Neural Systems and Rehabilitation Engineering 25.3 (2017): 227-234.

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