Human-machine interface based on multi-channel single-element ultrasound transducers: A preliminary study

Ultrasound (US) imaging is a promising sensing technique in the field of human-machine interface, and many positive results have been reported in literature on hand gesture recognition or finger angle prediction based on US imaging. However, in most of these studies, linear array ultrasound probes were used to generate US images, which made the US device expensive and bulky. In this paper, a method of extracting forearm muscle information via multiple single-element US transducers is proposed. By using this kind of transducers, a low-cost and small-size human-machine interface can be expected. Preliminary results show that an average recognition accuracy of 96% can be achieved for six motions, including five finger flexions and rest state.

[1]  Jing-Yi Guo,et al.  Dynamic monitoring of forearm muscles using one-dimensional sonomyography system. , 2008, Journal of rehabilitation research and development.

[2]  Honghai Liu,et al.  Performances of surface EMG and Ultrasound signals in recognizing finger motion , 2016, 2016 9th International Conference on Human System Interactions (HSI).

[3]  Jana Kosecka,et al.  Real-Time Classification of Hand Motions Using Ultrasound Imaging of Forearm Muscles , 2016, IEEE Transactions on Biomedical Engineering.

[4]  Honghai Liu,et al.  Multi-Modal Sensing Techniques for Interfacing Hand Prostheses: A Review , 2015, IEEE Sensors Journal.

[5]  Hong-Bo Xie,et al.  Towards the application of one-dimensional sonomyography for powered upper-limb prosthetic control using machine learning models , 2013, Prosthetics and orthotics international.

[6]  Xinjun Sheng,et al.  Improving robustness against electrode shift of high density EMG for myoelectric control through common spatial patterns , 2015, Journal of NeuroEngineering and Rehabilitation.

[7]  Jing-Yi Guo,et al.  Recognition of finger flexion motion from ultrasound image: a feasibility study. , 2012, Ultrasound in medicine & biology.

[8]  G. Farhat,et al.  Diagnostic ultrasound Imaging : Inside out , 2004 .

[9]  C. Castellini,et al.  Using Ultrasound Images of the Forearm to Predict Finger Positions , 2012, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[10]  Huzefa Rangwala,et al.  Novel Method for Predicting Dexterous Individual Finger Movements by Imaging Muscle Activity Using a Wearable Ultrasonic System , 2014, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[11]  Honghai Liu,et al.  A New Wearable Ultrasound Muscle Activity Sensing System for Dexterous Prosthetic Control , 2015, 2015 IEEE International Conference on Systems, Man, and Cybernetics.

[12]  Jing-Yi Guo,et al.  Performances of one-dimensional sonomyography and surface electromyography in tracking guided patterns of wrist extension. , 2009, Ultrasound in medicine & biology.

[13]  Qinghua Huang,et al.  Continuous Monitoring of Sonomyography, Electromyography and Torque Generated by Normal Upper Arm Muscles During Isometric Contraction: Sonomyography Assessment for Arm Muscles , 2008, IEEE Transactions on Biomedical Engineering.