Name: A Rehabilitation Program of Exoskeleton-assisted Body Weight-Supported Treadmill Training with Non-immersive Virtual Reality for Stroke Patients (Video) | JoVE Journal
Uploaded: 2025-05-16T12:20:00.000+00:00
Duration: 6 min
Description: Explore exoskeleton-assisted treadmill training with game-based virtual reality for stroke rehabilitation. This combined approach enhances balance, physical recovery, and cognitive engagement in early stroke recovery patients.

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5 minutes

The research project received funding from the Clinical Research Special Program of Peking Union Medical College Hospital with grant number 2022-PUMCH-B-053.

This research was a retrospective case series of inpatients recruited after stroke at Peking Union Medical College Hospital. This rehabilitation program was approved by the Institutional Review Board of Peking Union Medical College Hospital. Written informed consent was obtained from all patients prior to participation. The details of the equipment and software used in this study are listed in the Table of Materials.
1. Participant recruitment
<ol>
	<li>Enroll patients in the study following a rigorous screening process based on specific inclusion criteria. Organize the basic data of patients (see Table 1). These criteria are as follows:
	<ol>
		<li>Age: 20-65 years.</li>
		<li>Medical stability confirmed by a rehabilitation physician post-stroke (ischemic/hemorrhagic).</li>
		<li>A Modified Ashworth Scale (MAS) score of &#8804;2 (minimal muscle spasticity)2.</li>
		<li>Ability to walk 10 m with or without an assistive device to complete assessments, including the Berg Balance Scale (BBS), Timed Up-and-Go Test (TUG), and Functional Independence Measure (FIM)6.</li>
	</ol>
	</li>
	<li>Exclude patients with the following conditions:
	<ol>
		<li>Restriction in the range of motion (ROM) of the hip or knee joints.</li>
		<li>Presence of deep vein thrombosis (DVT).</li>
		<li>Mini-Mental State Examination (MMSE) score10 of less than 27 (cognitive impairment).</li>
		<li>Body weight exceeding 150 kg.</li>
		<li>Height exceeding 200 cm.</li>
	</ol>
	</li>
	<li>Re-screen patients prior to every treatment session. Terminate the trial if any of the following symptoms occur:
	<ol>
		<li>Altered consciousness: Sudden confusion, disorientation, or loss of consciousness.</li>
		<li>Breathing difficulties: Rapid breathing, shortness of breath, or other respiratory distress.</li>
		<li>Abnormal heart rate: Unusually high or low heart rate, palpitations, or an irregular heartbeat.</li>
		<li>Abnormal blood pressure: Significant increase or decrease in blood pressure, accompanied by dizziness or fainting.</li>
		<li>Airway obstruction: Coughing, choking, or sudden difficulty in breathing.</li>
		<li>Pain or discomfort: Severe pain, discomfort, or unusual sensations.</li>
	</ol>
	</li>
</ol>
2. Measurement
NOTE: These measurements are essential for properly fitting and customizing the exoskeleton, ensuring it provides optimal support. While the overall process is similar to other devices in the same category, details such as software operation, control buttons, and strap fastening may vary depending on the specific equipment.
<ol>
	<li>Take measurements while the patient is seated.
	<ol>
		<li>Measure the pelvic width using a flexible tape (ASIS to ASIS).</li>
		<li>Measure the upper leg length (greater trochanter to lateral femoral condyle).</li>
		<li>Measure the lower leg length (lateral malleolus to lateral femoral condyle).</li>
	</ol>
	</li>
	<li>Adjust the exoskeleton device based on the collected data. 
	NOTE: These adjustments are crucial for tailoring the exoskeleton to each patient&#39;s anatomy. Proper fit and alignment allow the device to effectively support and enhance mobility and rehabilitation.
	<ol>
		<li>Adjust the width using the turning handle (see Figure 2A) by increasing it 2-3 cm beyond the pelvic width.</li>
		<li>Pull the slot switch on the upper leg robotic arm (Figure 2B), adjust the length based on the measurements, and push the switch back in. Tighten the rotary switch to secure the arm. Align the knee joint with the device&#39;s motor for smooth, synchronized movement.</li>
		<li>Adjust the robotic arm of the lower leg following the procedure outlined in step 2.2.2.</li>
	</ol>
	</li>
	<li>Ensure the power supply is plugged in after adjusting the device to fit the patient&#39;s ergonomics. Assist the patient in wearing the device.</li>
</ol>
3. Donning the weight-supported system
<ol>
	<li>Turn the two handles counterclockwise (see Figure 2C) to loosen them, then pull the exoskeleton outward (see Figure 2D) to clear the treadmill runway and create space for the patient.</li>
	<li>Guide the patient onto the runway.
	<ol>
		<li>For walking patients: Guide them from the rear ramp to the front.</li>
		<li>For non-walking patients: Assist them in entering with a wheelchair and position them at the front.</li>
	</ol>
	</li>
	<li>Lower the harness (see Figure 2E) of the suspension system using the remote control (see Figure 2F). Adjust the harness to be flush with or slightly below the patient&#39;s torso, ensuring a proper fit.</li>
	<li>Unstrap the harness to facilitate dressing the patient. 
	NOTE: By following these steps, adjust the harness as needed to facilitate the dressing process for the patient, whether they are standing or in a wheelchair.
	<ol>
		<li>Patient standing: Apply the unfastened harness to the patient&#39;s torso from behind. Secure the straps comfortably around the torso. Position the leg straps around the thighs and fasten them securely.</li>
		<li>Patient in a wheelchair: Lift the patient&#39;s torso off the backrest. Thread the unbuckled harness around the torso from behind and secure the straps comfortably. Position the leg straps around the thighs and fasten them securely for a comfortable fit.</li>
	</ol>
	</li>
	<li>Elevate the weight-supported system to bring the patient into a standing position. Stop when the harness provides a slight tightening sensation. Adjust the weight reduction using the remote control and monitor the weight loss data on the unit (see Figure 2G). Raise the patient&#39;s body slightly to reduce weight while preventing the feet from hanging. 
	NOTE: Perform repeated elevation and lowering at any time during subsequent steps as needed for the patient&#39;s comfort and foot clearance without excessively reducing the patient&#39;s weight.
	<ol>
		<li>Patient standing: Use the remote control to gradually adjust the weight reduction based on the patient&#39;s condition.</li>
		<li>Patient in a wheelchair: Carefully lift the patient from the wheelchair and elevate them to a standing position using the ascending suspension system. Remove the wheelchair from the runway and adjust the patient&#39;s weight reduction with the remote control.</li>
	</ol>
	</li>
</ol>
4. Donning the exoskeleton
NOTE: By following these steps, the exoskeleton can be worn properly, providing the necessary support and stability for the patient during rehabilitation or exercise.
<ol>
	<li>Reset the outwardly opened exoskeleton back inward and rotate both handles clockwise to engage the immobilization device.</li>
	<li>Press down on the folded and suspended exoskeleton to transition it from a seated to a standing position (see Figure 2H).</li>
	<li>Instruct the patient to lean back against the torso of the exoskeleton and attach the thoracic anchorage straps.</li>
	<li>Adjust the height of the device to align the axis of the arm&#39;s motor with the patient&#39;s hip and knee joints.</li>
	<li>Tighten the belts to a comfortable level. Securely fasten the thigh and calf straps, ensuring they are appropriately tightened for the patient&#39;s comfort. 
	NOTE: This step is crucial to prevent equipment loosening during exercise and to ensure patient safety.</li>
	<li>Apply an ankle stabilizer if the patient has drop foot.</li>
</ol>
5. Operating the exoskeleton
<ol>
	<li>Access the control software on the computer and input the patient&#39;s basic information.</li>
	<li>Adjust the treatment duration, walking speed, and maximum allowable joint mobility for the hip and knee joints on both sides in the software interface. 
	NOTE: In this study, use the default joint range of motion settings, set the walking speed for patients at 1.5 km/h, and set the treatment duration to 20 min.</li>
	<li>Click on Start to initiate therapy. The exoskeleton and treadmill will begin operating together.</li>
</ol>
6. Opening the Game-based VR program
NOTE: Table 2 provides an overview of the games and their mechanics. Each game is designed to target specific lower extremity exercises tailored to meet the individual needs of patients for effective rehabilitation.
<ol>
	<li>Open the ZEPU Gait Training and Evaluation software on the computer. Select Game.</li>
	<li>Guide the patient during exoskeleton-assisted movement. When one leg is in the swing phase, instruct the patient to actively control it. When the leg is ready for propulsion, instruct the patient to forcefully propel it and perform hip flexion. 
	NOTE: The robotic arm&#39;s sensors will detect the patient&#39;s active torque, and feedback will be displayed in the game.</li>
	<li>Before the first session, explain the game interaction steps and principles to the patient. Provide a brief practice session with verbal reminders to help them understand when to apply active force during the correct gait phase. Begin formal therapy once the patient demonstrates the ability to use the device properly.</li>
</ol>
7. Removing the exoskeleton
NOTE: Ensure the safety and comfort of the patient throughout the removal process.
<ol>
	<li>Release the exoskeleton by unfastening the straps.</li>
	<li>Lift the exoskeleton into a suspended sitting position.</li>
	<li>Rotate the fixation handles (see Figure 2C) counterclockwise to release them.</li>
	<li>Unfold the exoskeleton outward to clear the runway, allowing for safe removal.</li>
</ol>
8. Removing the weight-supported system
<ol>
	<li>For walking patients: Lower the patient using the remote control, undo the straps, and assist them off the runway.</li>
	<li>For non-walking patients: Use the remote control to lower the patient into the wheelchair. Undo the straps and remove the weight reduction system. Guide the patient out of the runway.</li>
</ol>
9. Emergency
NOTE: If the patient exhibits any symptoms listed in steps1.3.1-1.3.6 during the treatment, stop the exercise and seek medical help immediately. Monitor the patient closely for symptoms and changes throughout rehabilitation.
<ol>
	<li>Locate the emergency stop device on the right-hand rail (see Figure 2I). Press and hold the button firmly to stop the equipment.</li>
	<li>Once the crisis has passed, restore the equipment by pulling the button upward.</li>
</ol>
10. Assessment and intervention
<ol>
	<li>Confirm that participants exhibit limited ambulatory ability and aim to achieve a higher functional level.</li>
	<li>Conduct pre-intervention assessments
	<ol>
		<li>Assess balance ability using the Berg Balance Scale (BBS), scoring from 0 (lowest) to 56 (highest)6.</li>
		<li>Evaluate gait using the Timed Up and Go (TUG) test6.</li>
		<li>Measure activities of daily living using the Functional Independence Measure (FIM)6.</li>
		<li>Perform all assessments 24 h before the first treatment session.</li>
	</ol>
	</li>
	<li>Administer the four-week intervention
	<ol>
		<li>Schedule 10 treatment sessions over 4 weeks.</li>
		<li>Conduct sessions on Mondays, Wednesdays, and Fridays during the first three weeks.</li>
		<li>Administer the final session on the Monday of the fourth week.</li>
		<li>Ensure all treatment sessions begin at 2:00 PM.</li>
	</ol>
	</li>
	<li>Implement the rehabilitation program
	<ol>
		<li>Train patients to use the rehabilitation program before the first session.</li>
		<li>Provide concise instructions through the game applications.</li>
		<li>Assign four games, each lasting 5 min, for a total of 20 min per session.</li>
		<li>Ensure patients engage independently with the program for the full 20 min.</li>
		<li>Set body weight support at 50% during each session.</li>
		<li>Allow maximal joint movement using the default joint range of motion settings.</li>
		<li>Set the walking speed at 1.5 km/h.</li>
	</ol>
	</li>
	<li>Conduct post-intervention assessments
	<ol>
		<li>Perform BBS, TUG, and FIM assessments 24 h after the final treatment session6.</li>
		<li>Ensure all clinical assessments are conducted by the same skilled and experienced physical therapist to maintain consistency.</li>
	</ol>
	</li>
</ol>
11. Statistical analyses
<ol>
	<li>Use statistical software to analyze the experimental results statistically.</li>
	<li>Apply the Shapiro-Wilk test to confirm that all outcome variables follow a normal distribution.</li>
	<li>Conduct a paired t-test for each outcome variable before and after treatment. Consider p &#60; 0.05 as the threshold for statistical significance.</li>
	<li>Use graphing software to create graphical representations of the data.</li>
</ol>

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<li>Zhang, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Chinese+Stroke+Association+guidelines+for+clinical+management+of+cerebrovascular+disorders%3A+executive+summary+and+2019+update+of+clinical+management+of+stroke+rehabilitation%5BTitle%5D)+AND+%22Stroke+Vasc+Neurol%22%5BJournal%5D)">Chinese Stroke Association guidelines for clinical management of cerebrovascular disorders: executive summary and 2019 update of clinical management of stroke rehabilitation.</a> Stroke Vasc Neurol. 5 (3), 250-259 (2020).</li>
<li>Calafiore, D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Efficacy+of+robotic+exoskeleton+for+gait+rehabilitation+in+patients+with+subacute+stroke%3A+a+systematic+review%5BTitle%5D)+AND+%22Eur+J+Phys+Rehabil+Med%22%5BJournal%5D)">Efficacy of robotic exoskeleton for gait rehabilitation in patients with subacute stroke: a systematic review.</a> Eur J Phys Rehabil Med. 58 (1), 1-8 (2022).</li>
<li>Chang, W. H., Kim, Y. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Robot-assisted+therapy+in+stroke+rehabilitation%5BTitle%5D)+AND+%22J+Stroke%22%5BJournal%5D)">Robot-assisted therapy in stroke rehabilitation.</a> J Stroke. 15 (3), 174-181 (2013).</li>
<li>Evans, R. W., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Robotic+locomotor+training+leads+to+cardiovascular+changes+in+individuals+with+incomplete+spinal+cord+injury+over+a+24-week+rehabilitation+period%3A+A+randomized+controlled+pilot+study%5BTitle%5D)+AND+%22Arch+Phys+Med+Rehabil%22%5BJournal%5D)">Robotic locomotor training leads to cardiovascular changes in individuals with incomplete spinal cord injury over a 24-week rehabilitation period: A randomized controlled pilot study.</a> Arch Phys Med Rehabil. 102 (8), 1447-1456 (2021).</li>
<li>Lyu, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Comparative+efficacy+of+gait+training+for+balance+outcomes+in+patients+with+stroke%3A+a+systematic+review+and+network+meta-analysis%5BTitle%5D)+AND+%22Front+Neurol%22%5BJournal%5D)">Comparative efficacy of gait training for balance outcomes in patients with stroke: a systematic review and network meta-analysis.</a> Front Neurol. 14, 1093779(2023).</li>
<li>Yamamoto, R., Sasaki, S., Kuwahara, W., Kawakami, M., Kaneko, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Effect+of+exoskeleton-assisted+body+weight-supported+treadmill+training+on+gait+function+for+patients+with+chronic+stroke%3A+a+scoping+review%5BTitle%5D)+AND+%22J+Neuroeng+Rehabil%22%5BJournal%5D)">Effect of exoskeleton-assisted body weight-supported treadmill training on gait function for patients with chronic stroke: a scoping review.</a> J Neuroeng Rehabil. 19 (1), 143(2022).</li>
<li>Hao, J., Xie, H., Harp, K., Chen, Z., Siu, K. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Effects+of+virtual+reality+intervention+on+neural+plasticity+in+stroke+rehabilitation%3A+a+systematic+review%5BTitle%5D)+AND+%22Arch+Phys+Med+Rehabil%22%5BJournal%5D)">Effects of virtual reality intervention on neural plasticity in stroke rehabilitation: a systematic review.</a> Arch Phys Med Rehabil. 103 (3), 523-541 (2022).</li>
<li>Akinci, M., Burak, M., Yasar, E., Kilic, R. T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((The+effects+of+robot-assisted+gait+training+and+virtual+reality+on+balance+and+gait+in+stroke+survivors%3A+A+randomized+controlled+trial%5BTitle%5D)+AND+%22Gait+Posture%22%5BJournal%5D)">The effects of robot-assisted gait training and virtual reality on balance and gait in stroke survivors: A randomized controlled trial.</a> Gait Posture. 103, 215-222 (2023).</li>
<li>Manuli, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Can+robotic+gait+rehabilitation+plus+virtual+reality+affect+cognitive+and+behavioural+outcomes+in+patients+with+chronic+stroke%3F+A+randomized+controlled+trial+involving+three+different+protocols%5BTitle%5D)+AND+%22J+Stroke+Cerebrovasc+Dis%22%5BJournal%5D)">Can robotic gait rehabilitation plus virtual reality affect cognitive and behavioural outcomes in patients with chronic stroke? A randomized controlled trial involving three different protocols.</a> J Stroke Cerebrovasc Dis. 29 (8), 104994(2020).</li>
<li>Mao, Y., Chen, P., Li, L., Li, L., Huang, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Changes+of+pelvis+control+with+subacute+stroke%3A+a+comparison+of+body-weight-support+treadmill+training+coupled+virtual+reality+system+and+over-ground+training%5BTitle%5D)+AND+%22Technol+Health+Care%22%5BJournal%5D)">Changes of pelvis control with subacute stroke: a comparison of body-weight-support treadmill training coupled virtual reality system and over-ground training.</a> Technol Health Care. 23 (Suppl 2), S355-S364 (2015).</li>
<li>Mubin, O., Alnajjar, F., Jishtu, N., Alsinglawi, B., Al Mahmud, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Exoskeletons+with+virtual+reality%2C+augmented+reality%2C+and+gamification+for+stroke+patients%27+rehabilitation%3A+Systematic+review%5BTitle%5D)+AND+%22JMIR+Rehabil+Assist+Technol%22%5BJournal%5D)">Exoskeletons with virtual reality, augmented reality, and gamification for stroke patients' rehabilitation: Systematic review.</a> JMIR Rehabil Assist Technol. 6 (2), e12010(2019).</li>
<li>Mirelman, A., Patritti, B. L., Bonato, P., Deutsch, J. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Effects+of+virtual+reality+training+on+gait+biomechanics+of+individuals+post-stroke%5BTitle%5D)+AND+%22Gait+Posture%22%5BJournal%5D)">Effects of virtual reality training on gait biomechanics of individuals post-stroke.</a> Gait Posture. 31 (4), 433-437 (2010).</li>
<li>Lee, H. J., Cho, K. H., Lee, W. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((The+effects+of+body+weight+support+treadmill+training+with+power-assisted+functional+electrical+stimulation+on+functional+movement+and+gait+in+stroke+patients%5BTitle%5D)+AND+%22Am+J+Phys+Med+Rehabil%22%5BJournal%5D)">The effects of body weight support treadmill training with power-assisted functional electrical stimulation on functional movement and gait in stroke patients.</a> Am J Phys Med Rehabil. 92 (12), 1051-1059 (2013).</li>
<li>Calabrò, R. S., Naro, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((The+role+of+virtual+reality+in+improving+motor+performance+as+revealed+by+EEG%3A+a+randomized+clinical+trial%5BTitle%5D)+AND+%22J+Neuroeng+Rehabil%22%5BJournal%5D)">The role of virtual reality in improving motor performance as revealed by EEG: a randomized clinical trial.</a> J Neuroeng Rehabil. 14 (1), 53(2017).</li>
<li>Lequerica, A. H., Kortte, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Therapeutic+engagement%3A+A+proposed+model+of+engagement+in+medical+rehabilitation%5BTitle%5D)+AND+%22Am+J+Phys+Med+Rehabil%22%5BJournal%5D)">Therapeutic engagement: A proposed model of engagement in medical rehabilitation.</a> Am J Phys Med Rehabil. 89 (5), 415-422 (2010).</li>
<li>Putrino, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Telerehabilitation+and+emerging+virtual+reality+approaches+to+stroke+rehabilitation%5BTitle%5D)+AND+%22Curr+Opin+Neurol%22%5BJournal%5D)">Telerehabilitation and emerging virtual reality approaches to stroke rehabilitation.</a> Curr Opin Neurol. 27 (6), 631-636 (2014).</li>
<li>Hidler, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Multicenter+randomized+clinical+trial+evaluating+the+effectiveness+of+the+Lokomat+in+subacute+stroke%5BTitle%5D)+AND+%22Neurorehabil+Neural+Repair%22%5BJournal%5D)">Multicenter randomized clinical trial evaluating the effectiveness of the Lokomat in subacute stroke.</a> Neurorehabil Neural Repair. 23 (1), 5-13 (2009).</li>
<li>Hornby, T. G., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Enhanced+gait-related+improvements+after+therapist-+versus+robotic-assisted+locomotor+training+in+subjects+with+chronic+stroke%3A+a+randomized+controlled+study%5BTitle%5D)+AND+%22Stroke%22%5BJournal%5D)">Enhanced gait-related improvements after therapist- versus robotic-assisted locomotor training in subjects with chronic stroke: a randomized controlled study.</a> Stroke. 39 (6), 1786-1792 (2008).</li>
<li>Westlake, K. P., Patten, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Pilot+study+of+Lokomat+versus+manual-assisted+treadmill+training+for+locomotor+recovery+post-stroke%5BTitle%5D)+AND+%22J+Neuroeng+Rehabil%22%5BJournal%5D)">Pilot study of Lokomat versus manual-assisted treadmill training for locomotor recovery post-stroke.</a> J Neuroeng Rehabil. 6, 18(2009).</li>
<li>Louie, D. R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Exoskeleton+for+post-stroke+recovery+of+ambulation+%28ExStRA%29%3A+Study+protocol+for+a+mixed-methods+study+investigating+the+efficacy+and+acceptance+of+an+exoskeleton-based+physical+therapy+program+during+stroke+inpatient+rehabilitation%5BTitle%5D)+AND+%22BMC+Neurol%22%5BJournal%5D)">Exoskeleton for post-stroke recovery of ambulation (ExStRA): Study protocol for a mixed-methods study investigating the efficacy and acceptance of an exoskeleton-based physical therapy program during stroke inpatient rehabilitation.</a> BMC Neurol. 20 (1), 35(2020).</li>
<li>Takebayashi, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Robot-assisted+training+as+self-training+for+upper-limb+hemiplegia+in+chronic+stroke%3A+a+randomized+controlled+trial%5BTitle%5D)+AND+%22Stroke%22%5BJournal%5D)">Robot-assisted training as self-training for upper-limb hemiplegia in chronic stroke: a randomized controlled trial.</a> Stroke. 53 (7), 2182-2191 (2022).</li>
</ol>

All authors declare no conflict of interest.

In this proposed intervention, a comprehensive treatment approach is presented that integrates a body weight support system and exoskeleton therapy supplemented by VR technology to facilitate dual-task training for individuals with stroke-related lower limb impairments. Treadmill training, when combined with other interventions, has been identified as having the greatest impact, particularly when applied before overground gait training, maximizing the training effect14. Robotic-assisted rehabilita...

In 2020, the approximate rates for stroke in mainland China were as follows: a prevalence rate of 2.6%, an incidence rate of 505.2 per 100,000 individuals annually, and a mortality rate of 343.4 per 1,00,000 individuals annually1. This debilitating condition causes functional disability, motor impairment, and dependence in 70%-80% of patients2. As walking is an essential component of human movement, it plays a crucial role in independent transfer, physiological well-being, and overall physical activity3. Therefore, restoring gait patterns in stroke patients is a critical goal of rehabilitation, as it ensures greater independence. While traditional methods have facilitated walking capability after stroke, technology-based therapy has made significant strides in stroke recovery in recent years, creating more intensive training models2. Moreover, technological advancements in stroke rehabilitation can further motivate and promote recovery in stroke survivors.
Lower limb exoskeleton (EXO) therapy is a promising and innovative approach to assist patients who cannot walk due to motor deficits in the lower limbs3. This therapy offers a high-dosage and high-intensity training program, allowing for earlier mobilization in a safer manner. Recent studies have demonstrated the potential benefits of this therapy for stroke patients, including improvements in muscle strength, balance, and walking capability4. Other studies comparing individuals with spinal cord injury indicate that both exoskeleton locomotor training and activity-based training significantly improve cardiovascular indices, with exoskeleton locomotor training showing greater effectiveness in enhancing cardiac responses to orthostatic stress and reducing standing heart rate5.
The robotic-assisted gait training system used in this study is designed to assist patients with walking rehabilitation. This robotic exoskeleton device, equipped with computerized engines at the hip and knee joints, enables patients to engage in passive or active-assisted walking, following different programmed gait patterns. The system includes a robotic framework that supports the patient&#39;s lower limbs while providing controlled assistance and resistance during walking. Feedback mechanisms are integrated into the system to guide the patient&#39;s movements and provide real-time data to clinicians, enhancing the motor learning process.
Body Weight-Supported Treadmill Training (BWSTT) is an assisted walking training system that combines a harness to partially support the patient&#39;s body weight and a motorized treadmill to facilitate movement6. The weight support system employed in this study uses a combination of slings and frames; the system redistributes a portion of the patient&#39;s body weight to the device, effectively lightening the weight burden during training. This adjustable weight support system encourages stroke patients with dependency or abnormal gait patterns to achieve a higher quality of gait. The patient can achieve better self-help control of the affected limb by reducing weight-bearing on the lower limb on the hemiplegic side. Additionally, the harness provides a secure means of preventing falls during early and intensive mobilization. BWSTT has shown remarkable potential in promoting balance skills, gait speed, and walking endurance across a wide range of functional walking levels in stroke patients7.
Game-based Virtual Reality (VR) training systems allow stroke patients to interact with objects and events in a realistic environment through recreational computer applications6,8. The virtual reality system used in this study does not rely on VR headsets but provides a basic virtual reality experience by using sensors on the exoskeleton to transmit the patient&#39;s movements into a virtual game environment displayed on a screen, simulating an interactive virtual reality scenario. This training system, which is more engaging and inspiring, increases preference and adherence among stroke survivors, potentially leading to more significant benefits compared to conventional physical training throughout the time-consuming recovery process. Moreover, VR rehabilitation as a surrogate intervention has demonstrated promising outcomes in improving gait, balance, cognitive capacity, and activities of daily living by providing dual-task training8. The current study demonstrated that VR, when used as an adjunct to robotic-assisted locomotor training, improved both balance and gait in chronic stroke patients, highlighting its potential to drive functional gains in ambulatory individuals with stroke9. Additionally, other research has indicated that robotic-assisted rehabilitation, particularly when integrated with VR, can enhance cognitive recovery and psychological well-being in individuals with chronic stroke10.
The therapeutic devices mentioned above can be effectively combined to create a distinct rehabilitation program tailored to each patient&#39;s needs. VR-assisted BWSTT, as a combination, appears feasible and promising. Research suggests it can reduce pelvic tilt and may outperform traditional gait training, especially with a modest intervention, aiding early hemiparetic patients11. Comparatively, there has been minimal exploration of the use of VR-integrated exoskeletons for lower limb rehabilitation in contrast to upper limb rehabilitation12. Mirelman et al. demonstrated the efficacy of combining exoskeletons with VR and video games for ankle and foot rehabilitation, resulting in enhanced walking velocity, improved paretic ankle motor control, increased peak plantarflexion moment, and greater ankle power generation13.
The combination of an exoskeleton with BWSTT and VR provides a comprehensive approach to stroke rehabilitation (see Figure 1). This integrated therapy combines the benefits of exoskeleton-assisted gait training, non-immersive VR technology, and the adjustable weight support provided by a treadmill. This approach has the potential to enhance motor recovery, balance, and overall functional outcomes for stroke patients6. While rehabilitation protocols utilizing these technologies have been explored in various research studies, the efficacy of combining exoskeleton-assisted BWSTT with game-based VR on dual-task capability in stroke survivors has rarely been studied. Therefore, this rehabilitation program aims to investigate the potential functions and advantages of this combination in enhancing walking capability during stroke recovery.

<table><tbody><tr><td>GraphPad Prism</td><td>https://www.graphpad.com/features</td><td></td><td></td></tr><tr><td>SPSS</td><td>IBP</td><td>version 18.0&amp;nbsp;</td><td></td></tr><tr><td>ZEPU Gait Training and Assessment System Software</td><td>Shandong ZEPU Medical Technology Co., Ltd.</td><td>V.1.0.1.2</td><td>The ZEPU Gait Training and Assessment System Software is designed to not only assess but also facilitate targeted gait rehabilitation, offering tailored therapeutic programs to improve mobility and functional outcomes for patients.</td></tr><tr><td>ZP-AIGen Gait Training System</td><td>Shandong ZEPU Medical Technology Co., Ltd.</td><td>ZEPU-AI1</td><td>Using neuroplasticity principles, the device simulates natural walking patterns, guiding patients through repetitive gait training to restore normal walking. The AI learns gait patterns, offering personalized treatment options. It monitors and records patient progress, helping to create customized treatment plans.</td></tr></tbody></table>

a rehabilitation program of exoskeleton-assisted body weight-supported treadmill training with non-immersive virtual reality for stroke patients

A Rehabilitation Program of Exoskeleton-assisted Body Weight-Supported Treadmill Training with Non-immersive Virtual Reality for Stroke Patients

Stroke is a cerebrovascular event that significantly affects patients' mobility and independence. Restoring gait patterns is a critical goal of stroke rehabilitation, and technology-based therapies have shown promising results. Lower limb exoskeleton therapy, body weight-supported treadmill training (BWSTT), and game-based virtual reality (VR) training are innovative approaches that have improved muscle strength, balance, and walking capability in stroke patients. Integrating these therapies into a comprehensive rehabilitation program may enhance motor recovery and functional outcomes for stroke survivors. This study investigates the potential advantages of combining exoskeleton-assisted BWSTT with game-based VR in enhancing dual-task capability during stroke recovery. Berg Balance Scale (BBS) demonstrated significant improvement after training (p = 0.03), but no statistical differences were observed in the Timed Up-and-Go Test (TUG, p = 0.15) and Functional Independence Measure (FIM, p = 0.38). In summary, this treatment has led to improvements in patient balance. The use of advanced technological devices in this rehabilitation protocol during the acute phase following a stroke is promising and warrants further investigation through a randomized controlled trial.

After completing a 4-week treatment without experiencing any adverse effects, the patient's progress was assessed, and the results were summarized in Table 3. The BBS score6 increased from 43.88 ± 3.80 to 48.38 ± 3.66, indicating a positive response. Both the TUG and FIM scores also showed improvement, with the TUG decreasing from 21.88 ± 5.62 to 17.63 ± 5.42 and the FIM increasing from 92.75 ± 12.80 to 98.75 ± 13.38.
The data (see ...

The efficacy of combining exoskeleton-assisted, body weight-supported treadmill training with game-based virtual reality on dual-task capability in stroke survivors has yet to be studied. Therefore, this rehabilitation program aims to investigate the potential functions and advantages of this combination in enhancing walking capability during stroke recovery.

Stroke is a cerebrovascular event that significantly affects patients' mobility and independence. Restoring gait patterns is a critical goal of stroke ...

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Research

JoVE Journal

Medicine

Recently, a vast amount of prospects have come available for human-robot interactive systems. In this paper we outline the integration of a new robotic device with open source software that can rapidly make possible a library of interactive functionality. We then outline a clinical application for a neurorehabilitation application.

Haptic/Graphic Rehabilitation: Integrating a Robot into a Virtual Environment Library and Applying it to Stroke Therapy

A novel low-cost human-machine interface for interactive post-stroke balance rehabilitation system is presented in this article. The system integrates off-the-shelf low-cost sensors towards volitionally driven electrotherapy paradigm. The proof-of-concept software interface is demonstrated on healthy volunteers.

A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation

Training a person with paralysis to ambulate using a powered exoskeleton may present challenges. The goals are to present the candidate selection criteria and the training procedures for exoskeletal-assisted walking and other mobility skills that can be progressed as the participant's skill level improves.

Training Persons with Spinal Cord Injury to Ambulate Using a Powered Exoskeleton

Here, we present a protocol to develop and apply a mobile game-based virtual reality program for the recovery of upper limb dysfunction in patients with stroke. The present study shows that the mobile program is feasible and effectively promotes upper limb recovery in stroke patients.

Mobile Game-based Virtual Reality Program for Upper Extremity Stroke Rehabilitation

This protocol demonstrates our model of activity-based locomotor treadmill training for rats with spinal cord injury (SCI). Included is both quadrupedal and forelimb-only groups, in addition to two distinct types of non-trained control groups. Investigators are able to assess training effects on SCI rats using this protocol.

Activity-based Training on a Treadmill with Spinal Cord Injured Wistar Rats

This study reports the development of a novel robot-assisted task-oriented program for hand rehabilitation. The developmental process consists of experiments using both healthy subjects and subjects who have had a stroke and suffered from subsequent motor control dysfunction.

Development of a Novel Task-oriented Rehabilitation Program using a Bimanual Exoskeleton Robotic Hand

Virtual reality (VR) is a powerful yet underutilized approach to advance the diagnosis and treatment of neurological disease. The Cleveland Clinic Virtual Reality Shopping platform combines state-of-the-art VR content with an omnidirectional treadmill to quantify instrumental activities of daily living-a proposed prodromal marker of neurological disease.

The Immersive Cleveland Clinic Virtual Reality Shopping Platform for the Assessment of Instrumental Activities of Daily Living

The current protocol outlines how the VR-based digital occupational training system enhances the rehabilitation of patients with cognitive impairment and upper limb dysfunction following a stroke.

Cognitive Function and Upper Limb Rehabilitation Training Post-Stroke Using a Digital Occupational Training System

Motor imagery in a virtual reality environment has wide applications in brain-computer interface systems. This manuscript outlines the use of personalized digital avatars that resemble the participants performing movements imagined by the participant in a virtual reality environment to enhance immersion and a sense of body ownership.

Motor Imagery Performance Through Embodied Digital Twins in a Virtual Reality-Enabled Brain-Computer Interface Environment

This protocol describes an upper limb rehabilitation robot that provides intelligent feedback through four modes. These modes enhance upper limb function and flexibility, thereby improving patients' quality of life.

Enhancing Upper Limb Function and Motor Skills Post-Stroke Through an Upper Limb Rehabilitation Robot

Explore exoskeleton-assisted treadmill training with game-based virtual reality for stroke rehabilitation. This combined approach enhances balance, physical recovery, and cognitive engagement in early stroke recovery patients.

A Rehabilitation Program of Exoskeleton-assisted Body Weight-Supported Treadmill Training with Non-immersive Virtual Reality for Stroke Patients (Video) | JoVE Journal

A Rehabilitation Program of Exoskeleton-assisted Body Weight-Supported Treadmill Training with Non-immersive Virtual Reality for Stroke Patients

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