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Amputation below the elbow (transradial amputation) is the most common form of major upper limb amputation, accounting for an estimated 40% of upper limb loss in the US. Most people who sustain transradial amputation are young and active, requiring a prosthetic limb that allows them to resume an active, productive lifestyle. Unfortunately, current prosthetic arms do not provide adequate function, and newer prostheses capable of many different hand grasps cannot be adequately controlled using current strategies.
In prior research, we have developed a surgical technique, called targeted muscle reinnervation (TMR), in which severed nerves that used to carry important control information to the missing limb are transferred to new 'target' muscles. After reinnervation, the target muscles contract whenever the individual attempts to move their missing arm, generating electrical EMG signals that can be used to control analogous movements in a prosthesis. Pattern recognition algorithms, also developed by our group, can decode this rich EMG information to enable intuitive control of many more functions. Combining TMR with pattern recognition in higher-level arm (transhumeral) amputees has resulted in substantially improved control that is more intuitive for the user.
Study Procedures
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We have finished recruiting subjects for this study and are currently in the process of analyzing data.
The goal of this multicenter study is to develop surgical techniques for transradial TMR and to evaluate the benefits of TMR in transradial amputees by performing clinical trials to compare pattern recognition control, before and after TMR, with a conventional control strategy. The median and ulnar nerves, which carry control information for intrinsic hand muscles involved in many hand grasps, will be transferred to forearm muscles. Subjects will use a state-of-the-art multifunction prosthesis-with either pattern recognition or conventional control-in activities of daily living during 8-week home trials, followed by comprehensive functional testing and user surveys.
We expect that TMR, when combined with pattern recognition, will allow transradial amputees to control more hand grasps more easily and more intuitively.
Outcome Measures
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Primary Outcome Measures
- Improved control of prosthesis as seen through functional use improvements.
Secondary Outcome Measures
- Modified Box and Blocks: Timed task to assess prosthetic control.
- Clothespin Relocation Test: Timed task to assess prosthetic control.
- ACMC: Assessment of capacity for myoelectric prosthetic control
- Jebsen Test of Hand Function: 7 part timed diagnostic test to determine the level of hand function.
- Southampton Hand Assessment Procedure (SHAP)
- OPUS-UEFS: An instrument that evaluates the activity limitations, quality of life, and patient satisfaction with services and devices.
- Activities Measure for Upper Limb Amputees (AM-ULA): A clinician rated measure of an upper limb amputee's performance of daily functional activities using a prosthesis.
- TAC TEST/ Motion Test: Virtual reality testing of classification accuracy, motion completion rate, motion completion time and path efficiency.
- PSFS: Used to assess functional ability to complete specific activities
Related Publications
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Simon AM, Turner KL, Miller LA, Hargrove LJ, Kuiken TA. Pattern recognition and direct control home use of a multi-articulating hand prosthesis. In 2019 IEEE 16th International Conference on Rehabilitation Robotics (ICORR) 2019 Jun 24 (pp. 386-391). IEEE.
Kuiken TA, Barlow AK, Hargrove L, Dumanian GA.. Techniques in orthopaedics (Rockville, Md.). 2017 Jun;32(2):109.
Funding Source
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Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD) Project No. 5R01HD081525-02
Study Team
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Todd Kuiken, MD, PhD, Principal Investigator
Kristi Turner, DHS, OTR/L
Annie Simon, PhD