Spinal Cord Injuries Clinical Trial
Official title:
Modeling, Optimization, and Control Methods for a Personalized Hybrid Walking Exoskeleton
The central objective of this study is to validate new algorithms that coordinate between functional electrical stimulation (FES) and the exoskeleton during sitting-to-standing, walking, and standing-to-sitting movements. The secondary objective is to optimize the algorithms as well as assess their ability to reduce FES-induced muscle fatigue by using ultrasound imaging as a sensing modality. This study will include persons with no disabilities and persons with Spinal Cord Injury (SCI). A research set-up comprising of a lower-limb exoskeleton and FES system will be used to achieve sitting-to-standing, walking, and standing-to-sitting movements. Ultrasound Imaging probes may be used to record muscle activity of the stimulated muscles. The signals derived from ultrasound will be used to optimize FES in order to reduce muscle fatigue as well as assess muscle fatigue.
Status | Not yet recruiting |
Enrollment | 30 |
Est. completion date | January 1, 2023 |
Est. primary completion date | January 1, 2023 |
Accepts healthy volunteers | Accepts Healthy Volunteers |
Gender | All |
Age group | 18 Years to 60 Years |
Eligibility |
Inclusion criteria for persons with SCI: 1. Participants will be men and women age 18-60 and have a primary diagnosis of complete or incomplete spinal cord injury, weigh less than 220 pounds (100kg), free from acute illness, and be at least 1 year post injury. 2. Individuals with injury between T-1 and T-10 level will be recruited (injury level for each participant will be assessed by a therapist on ASIA scale). 3. Medically stable with medical clearance for participation, no evidence of cardiopulmonary or pulmonary disease, severe spasticity, asymmetric hip positions. 4. Individuals who regularly bear weight bear during transfers (either with or without braces) so that we are using people who are accustomed to bearing weight on their lower limbs 5. The subjects who have experience in using some kind of walking assistive devices in the past or recently will be recruited. 6. Subjects must have at least one lower limb muscle group respond to FES. Inclusion criteria for persons without SCI: 1. Subjects will be included if they are between the ages of 18 and 60 and weigh less than 220 lbs (100kg). 2. Healthy, are able to walk normally, are able to sit patiently for 4 hours. 3. People who pass an assessment of safety by Dr. Cleveland. This would be a screen done by Dr. Cleveland after consent to determine if person is eligible. The proposed research will exclude children and pregnant women. We first aim to collect research data from adults as the proposed methods in the study have not been investigated on children and pregnant women. Exclusion criteria for persons with SCI: 1. Subjects with other neuromuscular disease such as polio, stroke or multiple sclerosis. 2. Persons with heart conditions and pacemakers will be excluded. 3. Concurrent severe medical disease, pressure sores, open wounds, existing infection, unstable spine, unhealed limb or pelvic fractures, history of recurrent fractures, known orthopedic injury to lower extremities, and osteoporosis. 4. Subjects with SCI who have open wounds, weight if with weight exceeds more than 220lb (100kg) 5. Subjects with SCI with insufficient knee or hip range of motion, i.e. contractures will be excluded. If someone has contractures it may not be possible, or safe, for them to be in the device. Persons who do not have following minimum joint angle range of motion: knee flexion from 0-80°, hip flexion from 0-45° and hip extension 0-10° will be excluded. 6. Subjects who find FES uncomfortable or painful; particularly, FES of the quadriceps muscle, hamstrings muscle, and ankle muscles. Exclusion criteria for persons without SCI: 1. A history of a neurological or an orthopedic disease that hampers normal lower limb movement 2. Persons with heart conditions and pacemakers will be excluded. 3. Any difficulty or an orthopedic condition that would impede knee extension 4. Absent sensation in lower leg 5. Subjects who find FES uncomfortable or painful; particularly, FES of the quadriceps muscle, hamstrings muscle, and ankle muscles. |
Country | Name | City | State |
---|---|---|---|
United States | 4212C Engineering Building III 1840 Entrepreneur Dr. | Raleigh | North Carolina |
Lead Sponsor | Collaborator |
---|---|
North Carolina State University | U.S. National Science Foundation, University of North Carolina, Chapel Hill |
United States,
Alibeji NA, Kirsch NA, Sharma N. A Muscle Synergy-Inspired Adaptive Control Scheme for a Hybrid Walking Neuroprosthesis. Front Bioeng Biotechnol. 2015 Dec 21;3:203. doi: 10.3389/fbioe.2015.00203. eCollection 2015. Review. — View Citation
Alibeji NA, Molazadeh V, Dicianno BE, Sharma N. A Control Scheme That Uses Dynamic Postural Synergies to Coordinate a Hybrid Walking Neuroprosthesis: Theory and Experiments. Front Neurosci. 2018 Apr 10;12:159. doi: 10.3389/fnins.2018.00159. eCollection 2018. — View Citation
Bao X, Kirsch N, Dodson A, Sharma N. Model Predictive Control of a Feedback-Linearized Hybrid Neuroprosthetic System With a Barrier Penalty. J Comput Nonlinear Dyn. 2019 Oct 1;14(10):101009-1010097. doi: 10.1115/1.4042903. Epub 2019 Sep 9. — View Citation
Kirsch N, Alibeji N, Fisher L, Gregory C, Sharma N. A semi-active hybrid neuroprosthesis for restoring lower limb function in paraplegics. Conf Proc IEEE Eng Med Biol Soc. 2014;2014:2557-60. doi: 10.1109/EMBC.2014.6944144. — View Citation
Kirsch NA, Bao X, Alibeji NA, Dicianno BE, Sharma N. Model-Based Dynamic Control Allocation in a Hybrid Neuroprosthesis. IEEE Trans Neural Syst Rehabil Eng. 2018 Jan;26(1):224-232. doi: 10.1109/TNSRE.2017.2756023. Epub 2017 Sep 22. — View Citation
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | Controls Algorithm Performance - Limb Angle Errors | The computer-controlled algorithms will get feedback from sensors that are inbuilt in the neuroprosthesis (exoskeleton). A motion capture system may also be used to measure joint angles so that spatiotemporal gait characteristics can be compared with the normal gait of a healthy control subject. Ultrasound imaging can be used as a tool to measure muscle fatigue induced by FES. The performance of the controls algorithm and success of the movements generated will be evaluated after this data is collected. | Through study completion, an average of 30 months. | |
Primary | Muscle fatigue Index to Measure FES-Induced Muscle Fatigue | The muscle fatigue index will be measured to assess muscle fatigue in a participant using the hybrid neuroprosthesis/exoskeleton. | Through study completion, an average of 30 months. | |
Secondary | Participant Verbal Feedback | We may ask the participant about their qualitative experience about the of our device and algorithms during the experiments. | Through study completion, an average of 30 months. |
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