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

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 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.

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's lower limbs while providing controlled assistance and resistance during walking. Feedback mechanisms are integrated into the system to guide the patient'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'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'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 applications^6,8. 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'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'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.

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

1. 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:
   1. Age: 20-65 years.
   2. Medical stability confirmed by a rehabilitation physician post-stroke (ischemic/hemorrhagic).
   3. A Modified Ashworth Scale (MAS) score of ≤2 (minimal muscle spasticity)².
   4. 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.
2. Exclude patients with the following conditions:
   1. Restriction in the range of motion (ROM) of the hip or knee joints.
   2. Presence of deep vein thrombosis (DVT).
   3. Mini-Mental State Examination (MMSE) score¹⁰ of less than 27 (cognitive impairment).
   4. Body weight exceeding 150 kg.
   5. Height exceeding 200 cm.
3. Re-screen patients prior to every treatment session. Terminate the trial if any of the following symptoms occur:
   1. Altered consciousness: Sudden confusion, disorientation, or loss of consciousness.
   2. Breathing difficulties: Rapid breathing, shortness of breath, or other respiratory distress.
   3. Abnormal heart rate: Unusually high or low heart rate, palpitations, or an irregular heartbeat.
   4. Abnormal blood pressure: Significant increase or decrease in blood pressure, accompanied by dizziness or fainting.
   5. Airway obstruction: Coughing, choking, or sudden difficulty in breathing.
   6. Pain or discomfort: Severe pain, discomfort, or unusual sensations.

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.

1. Take measurements while the patient is seated.
   1. Measure the pelvic width using a flexible tape (ASIS to ASIS).
   2. Measure the upper leg length (greater trochanter to lateral femoral condyle).
   3. Measure the lower leg length (lateral malleolus to lateral femoral condyle).
2. Adjust the exoskeleton device based on the collected data.
   NOTE: These adjustments are crucial for tailoring the exoskeleton to each patient's anatomy. Proper fit and alignment allow the device to effectively support and enhance mobility and rehabilitation.
   1. Adjust the width using the turning handle (see Figure 2A) by increasing it 2-3 cm beyond the pelvic width.
   2. 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's motor for smooth, synchronized movement.
   3. Adjust the robotic arm of the lower leg following the procedure outlined in step 2.2.2.
3. Ensure the power supply is plugged in after adjusting the device to fit the patient's ergonomics. Assist the patient in wearing the device.

3. Donning the weight-supported system

1. 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.
2. Guide the patient onto the runway.
   1. For walking patients: Guide them from the rear ramp to the front.
   2. For non-walking patients: Assist them in entering with a wheelchair and position them at the front.
3. 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's torso, ensuring a proper fit.
4. 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.
   1. Patient standing: Apply the unfastened harness to the patient's torso from behind. Secure the straps comfortably around the torso. Position the leg straps around the thighs and fasten them securely.
   2. Patient in a wheelchair: Lift the patient'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.
5. 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'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's comfort and foot clearance without excessively reducing the patient's weight.
   1. Patient standing: Use the remote control to gradually adjust the weight reduction based on the patient's condition.
   2. 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's weight reduction with the remote control.

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.

1. Reset the outwardly opened exoskeleton back inward and rotate both handles clockwise to engage the immobilization device.
2. Press down on the folded and suspended exoskeleton to transition it from a seated to a standing position (see Figure 2H).
3. Instruct the patient to lean back against the torso of the exoskeleton and attach the thoracic anchorage straps.
4. Adjust the height of the device to align the axis of the arm's motor with the patient's hip and knee joints.
5. Tighten the belts to a comfortable level. Securely fasten the thigh and calf straps, ensuring they are appropriately tightened for the patient's comfort.
   NOTE: This step is crucial to prevent equipment loosening during exercise and to ensure patient safety.
6. Apply an ankle stabilizer if the patient has drop foot.

5. Operating the exoskeleton

1. Access the control software on the computer and input the patient's basic information.
2. 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.
3. Click on Start to initiate therapy. The exoskeleton and treadmill will begin operating together.

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.

1. Open the ZEPU Gait Training and Evaluation software on the computer. Select Game.
2. 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's sensors will detect the patient's active torque, and feedback will be displayed in the game.
3. 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.

7. Removing the exoskeleton

NOTE: Ensure the safety and comfort of the patient throughout the removal process.

1. Release the exoskeleton by unfastening the straps.
2. Lift the exoskeleton into a suspended sitting position.
3. Rotate the fixation handles (see Figure 2C) counterclockwise to release them.
4. Unfold the exoskeleton outward to clear the runway, allowing for safe removal.

8. Removing the weight-supported system

1. For walking patients: Lower the patient using the remote control, undo the straps, and assist them off the runway.
2. 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.

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.

1. Locate the emergency stop device on the right-hand rail (see Figure 2I). Press and hold the button firmly to stop the equipment.
2. Once the crisis has passed, restore the equipment by pulling the button upward.

10. Assessment and intervention

1. Confirm that participants exhibit limited ambulatory ability and aim to achieve a higher functional level.
2. Conduct pre-intervention assessments
   1. Assess balance ability using the Berg Balance Scale (BBS), scoring from 0 (lowest) to 56 (highest)⁶.
   2. Evaluate gait using the Timed Up and Go (TUG) test⁶.
   3. Measure activities of daily living using the Functional Independence Measure (FIM)⁶.
   4. Perform all assessments 24 h before the first treatment session.
3. Administer the four-week intervention
   1. Schedule 10 treatment sessions over 4 weeks.
   2. Conduct sessions on Mondays, Wednesdays, and Fridays during the first three weeks.
   3. Administer the final session on the Monday of the fourth week.
   4. Ensure all treatment sessions begin at 2:00 PM.
4. Implement the rehabilitation program
   1. Train patients to use the rehabilitation program before the first session.
   2. Provide concise instructions through the game applications.
   3. Assign four games, each lasting 5 min, for a total of 20 min per session.
   4. Ensure patients engage independently with the program for the full 20 min.
   5. Set body weight support at 50% during each session.
   6. Allow maximal joint movement using the default joint range of motion settings.
   7. Set the walking speed at 1.5 km/h.
5. Conduct post-intervention assessments
   1. Perform BBS, TUG, and FIM assessments 24 h after the final treatment session⁶.
   2. Ensure all clinical assessments are conducted by the same skilled and experienced physical therapist to maintain consistency.

11. Statistical analyses

1. Use statistical software to analyze the experimental results statistically.
2. Apply the Shapiro-Wilk test to confirm that all outcome variables follow a normal distribution.
3. Conduct a paired t-test for each outcome variable before and after treatment. Consider p < 0.05 as the threshold for statistical significance.
4. Use graphing software to create graphical representations of the data.

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 Figure 3) showed that, when comparing pre-and post-assessment results, the BBS score demonstrated a significant improvement (p = 0.03, p < 0.05). Although no statistically significant differences were observed for TUG (p=0.15) and FIM (p=0.38), a trend of improvement was clinically noted (see Figure 4). These findings suggest that the treatment regimen significantly enhanced patients' balance, while improvements in gait and daily living skills did not reach statistical significance.

Figure 1: Exoskeleton-assisted body weight-supported treadmill training system combined with game-based virtual reality. (A) The training system integrates three devices, enabling patients to perform dual-task training while engaging in reduced-weight walking. (B) A patient undergoing EXO-BWSTT-VR therapy. Please click here to view a larger version of this figure.

Figure 2: Demonstration of operating procedures and equipment components. This figure provides an overview of key equipment components and procedures to enhance understanding of system operation. (A) Circular turning handle. (B) Robotic arm adjusted via a slot switch. (C) Circular turning handles. (D) Exoskeleton pulled outward (blue arrow). (E) Harness. (F) Remote control for adjusting patient elevation (+), lowering (-), increasing weight support (p), and decreasing weight support (q). (G) Weight support data display. (H) Exoskeleton pressed downward (blue arrow). (I) Emergency stop device. Please click here to view a larger version of this figure.

Figure 3: Changes in outcome measures at the end of treatment. (A) Change in Berg Balance Scale (BBS) score (n = 8). (B) Change in Timed Up-and-Go (TUG) test results (n = 8). (C) Change in Functional Independence Measure (FIM) score (n = 8). Measurements were taken before treatment (Pre) and two weeks after treatment (Post) with EXO-BWSTT-VR therapy. Error bars represent standard deviation (SD). *p < 0.05; ns: not significant. Please click here to view a larger version of this figure.

Figure 4: Trendline of outcome measures before and after treatment for each patient. (A) Change in BBS score. (B) Change in TUG test results. (C) Change in FIM score. Please click here to view a larger version of this figure.

Table 1: Demographic and clinical characteristics of participants. Abbreviations: SD = standard deviation; I = ischemic; H = hemorrhagic; MMSE = Mini-Mental State Examination; Y = yes; N = no.

Table 2: Game content and gameplay of the game-based virtual reality program. Each game application is designed for specific task-oriented exercises, with difficulty levels customized based on the lower extremity function of each patient.

Table 3: Baseline and four-week functional scale assessments and tests. Abbreviations: BBS = Berg Balance Scale; TUG = Timed Up-and-Go Test; FIM = Functional Independence Measure. *Paired t-test. Data are presented as mean ± SD (range).

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 rehabilitation, based on motor learning principles, utilizes VR feedback and avatar-guided exercises to activate the mirror system, enhancing motor learning and inducing significant cortical and subcortical changes at the cellular and synaptic levels¹⁵.

In neurological rehabilitation, the level of engagement during therapy significantly influences active participation, an effect particularly evident when compared to treatment solely involving exoskeleton robots like Ekso or ReWalk¹⁶. Given the close interconnection between the motor and cognitive domains, combining multiple intervention strategies appears to be a promising approach. The integration of intensive, repetitive motor training with VR-based feedback and dual-task exercises likely influences sensory-motor integration areas, contributing to enhanced motor and cognitive recovery¹⁰. Consequently, the integration of gamification techniques into established neurorehabilitation models to increase participant engagement has gained prominence in recent years¹⁷.

Although cognitive function was not directly assessed, the interactive elements of the game introduced cognitive challenges that increased the complexity of training. Through the synergistic interaction of games and devices, the creation of a simulated environment has the potential to enhance patient engagement, making otherwise repetitive rehabilitation exercises more enjoyable and sustainable.

However, according to previous research, not all results are optimistic. Some scholars believe that ambulatory individuals with stroke may experience poorer rehabilitation outcomes when confined to robotic or harness systems¹⁸. Hornby et al. found that among forty-eight ambulatory chronic stroke survivors stratified by severity of locomotor deficits, therapist-assisted locomotor training resulted in greater improvements in walking ability compared to a similar dosage of robotic-assisted locomotor training¹⁹. Meanwhile, Westlake et al. reported that while primary outcomes were similar between the Lokomat and manual BWSTT groups after training, the Lokomat group showed improvements in self-selected walking speed, paretic step length ratio, and four secondary measures, whereas the manual group primarily enhanced their balance scores²⁰.

A factor contributing to the variability in findings could be the heterogeneity of participant populations. Differences in age, severity of impairment, and prior rehabilitation experiences may influence the effectiveness of exo-BWSTT, leading to inconsistent results across studies. Additionally, the duration and intensity of exo-BWSTT interventions varied significantly. Short-term or less intensive protocols might not demonstrate the full potential of the technology, whereas longer or more intensive interventions may yield more substantial benefits, which could explain some of the discrepancies in reported outcomes.

This treatment protocol aims to complement or potentially replace conventional rehabilitation programs. The primary goal of this intervention is to enhance motor function and promote greater independence in stroke patients. By combining innovative technologies and therapeutic strategies, rehabilitation outcomes can be optimized, ultimately improving the overall quality of life for individuals affected by stroke.

Further practical implementation is required to design exercise prescriptions for patients, including determining training duration, frequency, walking speed progression, game selection and combination, and game difficulty adjustments. Additionally, personalized weight-supported prescriptions tailored to individual patients should be explored in future clinical practice. The integration of rehabilitation devices with traditional physical therapy and the gradual reduction in device usage frequency upon reaching specific walking improvement goals should also be considered in future rehabilitation protocols²¹. Ultimately, the aim is to develop a more comprehensive clinical practice program that meets the personalized needs of stroke patients.

The study design has certain limitations. Firstly, it is a retrospective case series with a self-control design before and after patient intervention, lacking a proper experimental control group. This limits the ability to determine whether this system is more effective than traditional physical therapy methods. Secondly, the relatively small sample size may restrict the generalizability of the findings and reduce the statistical power to detect significant differences. Additionally, due to the selection of assessment tools, patients with poor standing and walking skills were not included in this study.

Furthermore, the inherent variability in hospital stay lengths among patients restricted the intervention to only 10 sessions. This limited timeframe may not have been sufficient to observe the full potential benefits of the treatment. Including subsequent outpatient treatments and follow-up assessments would have been beneficial in evaluating the long-term effects and sustainability of the intervention.

This study demonstrates the beneficial effects of the rehabilitation program on walking ability, balance, independence, and daily functional levels in stroke patients. Additionally, it highlights the research value of the combined device, EXO-BWSTT-VR, in stroke rehabilitation. Although extensive literature exists on robotic systems in rehabilitation, this study represents only a fraction of this body of work. The wide variety of robotic devices and treatment protocols in existing studies limits the generalizability of these findings.

While systematic reviews and meta-analyses have explored treatment frequency and intensity, no standardized treatment programs based on these findings currently exist. For instance, some studies on upper limb robotic rehabilitation recommend administering robotic therapies three times a week for 10 weeks, with each session lasting 60 min²². However, treatment protocols vary widely across studies, and this lack of standardization is a limitation of this study. Future research should focus on establishing more consistent treatment guidelines based on existing evidence. Additionally, future investigations should aim to conduct more precise, detailed, and well-designed experiments to explore these aspects further.

All authors declare no conflict of interest.

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