Title
New Multi-Channel Transcutaneous Electrical Stimulation Technology For Rehabilitation
Abstract
Transcutaneous (surface) electrical stimulation (TES) is a widely applied technique for muscle atrophy treatment, muscle force training, endurance training, pain treatment, functional movement therapy, and the restoration of motor functions. We present a new TES technology based on a multi-channel stimulation approach, which allows us to perform real-time spatial and temporal variations of the electrical current density on the skin surface and in deeper tissue layers. This new approach can generate a better muscle selectivity and improved muscle activation patterns compared to state of art TES systems, which operate with predetermined electrode positions.In simulations using a finite element model (FEM) of the distal arm we could show that the nerve activation in the muscle layer is not significantly influenced by the structure of the multi-channel electrode, if the gap between elements is less than 2 mm. Experiments in healthy volunteers allowed us to measure the selectivity of single finger activations. We could also show in stroke subjects that this novel multi-channel approach was able to generate selective finger and wrist extension movements that were strong enough to overcome flexion hyperactivity.For future applications in rehabilitation a full integration of the stimulation hardware into a garment sleeve would be helpful. Once fully integrated, this new technology has a high potential to increase the ease of use, stimulation and wear comfort. It is able to improve muscle selectivity compared to state of the art TES systems, and allows the implementation of a variety of new applications for the medical and consumer market.
Year
DOI
Venue
2006
10.1109/IEMBS.2006.259399
2006 28TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-15
Keywords
DocType
Volume
ease of use,finite element model,real time,endurance training,current density,finite element analysis,biomechanics,motor function
Conference
1
ISSN
Citations 
PageRank 
1557-170X
2
0.69
References 
Authors
0
4
Name
Order
Citations
PageRank
Thierry Keller192.66
Marc Lawrence2133.03
Andreas Kuhn3133.03
Manfred Morari46006918.33