Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Regen is a robot-assisted device designed to help therapists and improve the quality of treatment. It works by replicating the movement of the therapist and providing assistance as needed for the patient. This study aims to assess the safety, feasibility, usability, and ability to Regen to replicate the movement pattern of therapist in young healthy adults during treadmill walking.
Physical therapy, despite its effectiveness, is a physically demanding profession that requires moderate to high physical and psychological work demands. A single session typically lasts close to an hour per patient, with a substantial portion dedicated to hands-on rehabilitation therapy, excluding assessment. Long sessions, repetitive manual motions, and awkward postures contribute to fatigue, risk of musculoskeletal strain, and limited treatment duration.
One of such physically demanding tasks in rehabilitation is gait training, which often requires therapists to provide continuous manual assistance to a patient's lower limbs during treadmill walking or overground training. This repetitive, non-ergonomic work not only accelerates therapist fatigue and low back pain but also restricts the number of gait cycles that can be practiced, thereby limiting patient outcomes. These challenges create a growing need for robotic technology that can share the physical workload while maintaining therapy quality.
Rehabilitation robotic technology ranges from exoskeletons to end-effector-based assisted training devices. These provide precision, repeatability, and adaptability beyond traditional therapy methods, while also providing sensory and motor feedback. Despite these advantages, current robotic devices still face significant barriers to widespread adoption. Most rehabilitation robots either provide fixed-repetitive motions, work on just one joint, or require extensive pre-programming, which limits adaptability and versatility to individual patient needs. Further, high equipment costs, the need for specialized staff training, and required adaptations to clinical infrastructure often limit their accessibility and scalability.
Regen offers a potential solution to these gaps. Regen is a medical robotic technology aimed at improving the strength and mobility of patients. This device consists of a human-interactive robot arm that connects patients via an arm or leg brace, providing therapeutic motions to patients. It works by replicating therapist-guided movements, extending therapy duration, and ensuring consistent motion delivery. Regen is unique in its "assist-as-needed" capability. This allows the therapist to directly teach and calibrate new trajectories for each user, set repetitions, and then run based on the patient's abilities. This adaptability not only supports patient progression but also enhances motivation for the patient. Thus, the system is more responsive to the real-world variability of therapy sessions.
Before such systems can be brought into clinical practice, it is essential to evaluate usability and validity. Usability assesses whether the system is acceptable, safe, and easy to use for both therapists and patients. Validity assesses the system's ability to accurately replicate therapeutic movement trajectories.
The primary aim of this study is to evaluate the feasibility and usability of Regen in young healthy adults. The secondary aim is to assess the validity of the device in replicating therapist-guided movement using a marker-based motion capture system. The investigators hypothesize that Regen is a safe, usable, and valid tool for delivering therapist-like rehabilitation movements.
Not provided
Not provided
Not provided
Not provided
Not provided
| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Regen-assisted gait feasibility and usability arm | Experimental | Single experimental arm in which all participants complete treadmill walking under therapist-assisted and Regen-assisted conditions, to evaluate the feasibility and usability of the Regen robotic gait therapy system. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Regen Rehabilitation Assistive Device | Device | Regen is a robotic gait therapy device that learns therapist-guided movement trajectories and autonomously reproduces them. |
|
| Measure | Description | Time Frame |
|---|---|---|
| System Usability Scale (SUS) | The System Usability Scale (SUS) will be used to assess the usability of the device. The SUS consists of 10 items scored on a 5-point Likert scale and converted to a total score ranging from 0 to 100, with higher scores indicating better usability. | During the experimental session (Day 1) and immediately post-task (within 10 minutes after completion) |
| NASA Task Load Index (NASA-TLX) | The NASA Task Load Index (NASA-TLX) will be used to assess perceived workload across six domains (mental demand, physical demand, temporal demand, performance, effort, and frustration). Scores range from 0 to 100, with higher scores indicating greater workload. | During the experimental session (Day 1) and immediately post-task (within 10 minutes after completion) |
| Device Acceptability (Likert Scale) | Participants will rate safety, comfort, ease of use, and satisfaction using 5-point Likert scale items. Higher scores indicate greater acceptability of the device. | Immediately post-task (within 10 minutes after completion, Day 1) |
| Qualitative Feedback on Device Usability and Safety | Open-ended questions will be used to collect qualitative feedback from participants and therapists regarding device usability, safety, and overall experience. | Immediately post-task (within 10 minutes after completion, Day 1) |
Not provided
Not provided
Inclusion Criteria:
Exclusion Criteria:
(1) For healthy study participants:
(2) For PT:
Not provided
Not provided
Not provided
Not provided
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Mac Prible, PhD | Contact | 6466208829 | prible@utexas.edu | |
| Sonu Maharjan, MS | Contact | 6823743674 | sm86245@my.utexas.edu |
| Name | Affiliation | Role |
|---|---|---|
| Hao-Yuan Hsiao, PhD | University of Austin at Texas | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| University of Texas at Austin | Recruiting | Austin | Texas | 78712 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 34271954 | Background | Zbytniewska M, Kanzler CM, Jordan L, Salzmann C, Liepert J, Lambercy O, Gassert R. Reliable and valid robot-assisted assessments of hand proprioceptive, motor and sensorimotor impairments after stroke. J Neuroeng Rehabil. 2021 Jul 16;18(1):115. doi: 10.1186/s12984-021-00904-5. | |
| 33668987 | Background | Giansanti D. The Social Robot in Rehabilitation and Assistance: What Is the Future? Healthcare (Basel). 2021 Feb 25;9(3):244. doi: 10.3390/healthcare9030244. |
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| 39273744 | Background | Banyai AD, Brisan C. Robotics in Physical Rehabilitation: Systematic Review. Healthcare (Basel). 2024 Aug 29;12(17):1720. doi: 10.3390/healthcare12171720. |
| 35784252 | Background | Jing Q, Xing Y, Duan M, Guo P, Cai W, Gao Q, Gao R, Ji L, Lu J. Study on the Rehabilitation Therapist Estimation Under Institutional Perspective by Applying the Workload Indicators of Staffing Needs in the Aging Context. Front Public Health. 2022 Jun 16;10:929675. doi: 10.3389/fpubh.2022.929675. eCollection 2022. |