The provision of continuous passive, and intent-based assisted movements for neuromuscular training can be incorporated into a robotic elbow sleeve. The objective of this study is to propose the design and test the functionality of a soft robotic elbow sleeve in assisting flexion and extension of the elbow, both passively and using intent-based motion reinforcement. First, the elbow sleeve was developed, using elastomeric and fabric-based pneumatic actuators, which are soft and lightweight, in order to address issues of non-portability and poor alignment with joints that conventional robotic rehabilitation devices are faced with. Second, the control system was developed to allow for: (i) continuous passive actuation, in which the actuators will be activated in cycles, alternating between flexion and extension; and (ii) an intent-based actuation, in which user intent is detected by surface electromyography (sEMG) sensors attached to the biceps and triceps, and passed through a logic sequence to allow for flexion or extension of the elbow. Using this setup, the elbow sleeve was tested on six healthy subjects to assess the functionality of the device, in terms of the range of motion afforded by the device while in the continuous passive actuation. The results showed that the elbow sleeve is capable of achieving approximately 50% of the full range of motion of the elbow joint among all subjects. Next, further experiments were conducted to test the efficacy of the intent-based actuation on these healthy subjects. The results showed that all subjects were capable of achieving electromyography (EMG) control of the elbow sleeve. These preliminary results show that the elbow sleeve is capable of carrying out continuous passive and intent-based assisted movements. Further investigation of the clinical implementation of the elbow sleeve for the neuromuscular training of neurologically-impaired persons, such as stroke survivors, is needed.
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http://dx.doi.org/10.3389/fnins.2017.00597 | DOI Listing |
BMC Neurol
November 2024
Department of Neurosciences, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK.
Sensors (Basel)
July 2024
Department of Mechanical Engineering, Department of Materials Science and Engineering, and Center for Composite Materials, University of Delaware, Newark, DE 19716, USA.
Physical therapy is often essential for complete recovery after injury. However, a significant population of patients fail to adhere to prescribed exercise regimens. Lack of motivation and inconsistent in-person visits to physical therapy are major contributing factors to suboptimal exercise adherence, slowing the recovery process.
View Article and Find Full Text PDFJBJS Case Connect
July 2024
Department of Orthopaedic Surgery, Pediatric Orthopaedic Surgery, Medical College of Wisconsin, Milwaukee, Wisconsin.
Case: A 12-year-old girl presented with significant right elbow pain following a fall during soccer which caused an osseous triceps avulsion injury and nondisplaced type II Salter-Harris radial neck fracture. The patient was treated with successful open repair utilizing suture anchor fixation, resulting in full return of function and return to previous activities.
Conclusion: Timely and accurate diagnosis and treatment of displaced triceps sleeve avulsion injuries is critical and can result in excellent patient outcomes and return to previous functional level.
J Shoulder Elbow Surg
December 2024
Department of Physical Therapy, Akita University Graduate School of Health Sciences, Akita, Japan.
Background: The forearm flexor-pronator muscles act as a dynamic elbow stabilizer against elbow valgus load during baseball pitching. The elasticity of these muscles increases with pitching. However, it is unclear whether increased muscle elasticity is associated with greater elbow valgus torque during pitching.
View Article and Find Full Text PDFSensors (Basel)
June 2024
Department of Electrical and Computer Engineering, New York Institute of Technology, New York, NY 10023, USA.
This work presents a novel approach for elbow gesture recognition using an array of inductive sensors and a machine learning algorithm (MLA). This paper describes the design of the inductive sensor array integrated into a flexible and wearable sleeve. The sensor array consists of coils sewn onto the sleeve, which form an LC tank circuit along with the externally connected inductors and capacitors.
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