Using Large-Scale Sensor Data to Test Factors Predictive of Perseverance in Home Movement Rehabilitation: Early exercise frequency and schedule consistency.

Home-based exercises are an important component of stroke rehabilitation but are seldom fully completed. Past studies of exercise perseverance in the general public have suggested the importance of early exercise frequency and schedule consistency (in terms of which days of the week exercises are performed) because they encourage habit formation. To test whether these observations apply after a stroke, we leveraged data from 2,583 users of a sensor-based system (FitMi) developed to motivate movement exercises at home. We grouped users based on their early exercise frequency (defined across the initial 6 weeks of use) and calculated the evolution of habit score (defined as exercise frequency multiplied by exercise duration) across 6 months. We found that habit score decayed exponentially over time but with a slower decay constant for individuals with higher early frequency. Only the group with an early exercise frequency of 4 days/week or more had non-zero habit score at six months. Within each frequency group, dividing individuals into higher and lower consistency subgroups revealed that the higher consistency subgroups had significantly higher habit scores. These results are consistent with previous studies on habit formation in exercise and may help in designing effective home rehabilitation programs after stroke.

A single-center, assessor-blinded, randomized controlled clinical trial to test the safety and efficacy of a novel brain-computer interface controlled functional electrical stimulation (BCI-FES) intervention for gait rehabilitation in the chronic stroke population.

BACKGROUND: In the United States, there are over seven million stroke survivors, with many facing gait impairments due to foot drop. This restricts their community ambulation and hinders functional independence, leading to several long-term health complications. Despite the best available physical therapy, gait function is incompletely recovered, and this occurs mainly during the acute phase post-stroke. Therapeutic options are limited currently. Novel therapies based on neurobiological principles have the potential to lead to long-term functional improvements. The Brain-Computer Interface (BCI) controlled Functional Electrical Stimulation (FES) system is one such strategy. It is based on Hebbian principles and has shown promise in early feasibility studies. The current study describes the BCI-FES clinical trial, which examines the safety and efficacy of this system, compared to conventional physical therapy (PT), to improve gait velocity for those with chronic gait impairment post-stroke. The trial also aims to find other secondary factors that may impact or accompany these improvements and establish the potential of Hebbian-based rehabilitation therapies. METHODS: This Phase II clinical trial is a two-arm, randomized, controlled, longitudinal study with 66 stroke participants in the chronic (> 6 months) stage of gait impairment. The participants undergo either BCI-FES paired with PT or dose-matched PT sessions (three times weekly for four weeks). The primary outcome is gait velocity (10-meter walk test), and secondary outcomes include gait endurance, range of motion, strength, sensation, quality of life, and neurophysiological biomarkers. These measures are acquired longitudinally. DISCUSSION: BCI-FES holds promise for gait velocity improvements in stroke patients. This clinical trial will evaluate the safety and efficacy of BCI-FES therapy when compared to dose-matched conventional therapy. The success of this trial will inform the potential utility of a Phase III efficacy trial. TRIAL REGISTRATION: The trial was registered as "BCI-FES Therapy for Stroke Rehabilitation" on February 19, 2020, at clinicaltrials.gov with the identifier NCT04279067.

Uncovering clinical rehabilitation technology trends: field observations, mixed methods analysis, and data visualization.

Objective: To analyze real-world rehabilitation technology (RT) use, with a view toward enhancing RT development and adoption. Design: A convergent, mixed-methods study using direct field observations, semi-structured templates, and summative content analysis. Setting: Ten neurorehabilitation units in a single health system. Participants: 3 research clinicians (1OT, 2PTs) observed ∼60 OTs and 70 PTs in inpatient; ∼18 OTs and 30 PTs in outpatient. Interventions: Not applicable. Main Outcome Measures: Characteristics of RT, time spent setting up and using RT, and clinician behaviors. Results: 90 distinct devices across 15 different focus areas were inventoried. 329 RT-uses were documented over 44 hours with 42% of inventoried devices used. RT was used more during interventions (72%) than measurement (28%). Intervention devices used frequently were balance/gait (39%), strength/endurance (30%), and transfer/mobility training (16%). Measurement devices were frequently used to measure vitals (83%), followed by grip strength (7%), and upper extremity function (5%). Device characteristics were predominately AC-powered (56%), actuated (57%), monitor-less (53%), multi-use (68%), and required little familiarization (57%). Set-up times were brief (mean ± SD = 3.8±4.21 and 0.8±1.3 for intervention and measurement, respectively); more time was spent with intervention RT (25.6±15) than measurement RT (7.3±11.2). RT nearly always involved verbal instructions (72%) with clinicians providing more feedback on performance (59.7%) than on results (30%). Therapists' attention was split evenly between direct attention towards the patient during clinician treatment (49.7%) and completing other tasks such as documentation (50%). Conclusions: Even in a tech-friendly hospital, majority of available RT were observed un-used, but identifying these usage patterns is crucial to predict eventual adoption of new designs from earlier stages of RT development. An interactive data visualization page supplement is provided to facilitate this study.

Robotically quantifying finger and ankle proprioception: Role of range, speed, anticipatory errors, and learning.

Proprioception plays a key role in motor control and stroke recovery. Robotic devices are increasingly being used to improve proprioceptive assessments, but there is a lack of knowledge about how programmable factors such as testing range, speed, and prior exposure affect tests. From a physiological standpoint, such factors may regulate the sensitivity of limb proprioceptors, thereby influencing assessment results when not controlled for. To determine the relative influence of such factors, we studied the Crisscross proprioceptive assessment, a recently developed robotic assessment that requires participants to indicate when two joints pass by each other as they are moved passively by the robot. We implemented Crisscross with novel robots for the fingers and ankles and tested young unimpaired participants in single sessions (N = 16) and longitudinally (N = 5, across 15-30 sessions over 3-10 weeks). In single-session testing, we found that proprioceptive acuity was better for the fingers than the ankle (p < 0.01). For both limbs, acuity improved near the ends of the range of motion, which may be due to greater involvement of load and joint receptors. Acuity was poorer for slower movements due to greater anticipatory errors. These results show how the range and speed selected for a proprioceptive test affect proprioceptive acuity and highlight the heightened role of anticipatory errors at slow speeds. Improvements in proprioceptive acuity were not detectable in a single session, but acuity improved across multiple testing sessions (p < 0.01). This result shows that multiple prior exposure over at least several days can affect acuity.Clinical Relevance- Proprioceptive assessments should account for range and speed, which could be enabled by leveraging robotics technology. Proprioceptive acuity can be improved through repeated testing, an observation that is relevant to proprioceptive rehabilitation as well.

A Systematic Review of the Learning Dynamics of Proprioception Training: Specificity, Acquisition, Retention, and Transfer.

OBJECTIVE: We aimed to identify key aspects of the learning dynamics of proprioception training including: 1) specificity to the training type, 2) acquisition of proprioceptive skills, 3) retention of learning effects, and 4) transfer to different proprioceptive skills. METHODS: We performed a systematic literature search using the database (MEDLINE, EMBASE, Cochrane Library, and PEDro). The inclusion criteria required adult participants who underwent any training program that could enhance proprioceptive function, and at least 1 quantitative assessment of proprioception before and after the intervention. We analyzed within-group changes to quantify the effectiveness of an intervention. RESULTS: In total, 106 studies with 343 participant-outcome groups were included. Proprioception-specific training resulted in large effect sizes with a mean improvement of 23.4 to 42.6%, nonspecific training resulted in medium effect sizes with 12.3 to 22% improvement, and no training resulted in small effect sizes with 5.0 to 8.9% improvement. Single-session training exhibited significant proprioceptive improvement immediately (10 studies). For training interventions with a midway evaluation (4 studies), trained groups improved by approximately 70% of their final value at the midway point. Proprioceptive improvements were largely maintained at a delayed follow-up of at least 1 week (12 studies). Finally, improvements in 1 assessment were significantly correlated with improvements in another assessment (10 studies). CONCLUSIONS: Proprioceptive learning appears to exhibit several features similar to motor learning, including specificity to the training type, 2 time constant learning curves, good retention, and improvements that are correlated between different assessments, suggesting a possible, common mechanism for the transfer of training.

Counting Finger and Wrist Movements Using Only a Wrist-Worn, Inertial Measurement Unit: Toward Practical Wearable Sensing for Hand-Related Healthcare Applications.

The ability to count finger and wrist movements throughout the day with a nonobtrusive, wearable sensor could be useful for hand-related healthcare applications, including rehabilitation after a stroke, carpal tunnel syndrome, or hand surgery. Previous approaches have required the user to wear a ring with an embedded magnet or inertial measurement unit (IMU). Here, we demonstrate that it is possible to identify the occurrence of finger and wrist flexion/extension movements based on vibrations detected by a wrist-worn IMU. We developed an approach we call "Hand Activity Recognition through using a Convolutional neural network with Spectrograms" (HARCS) that trains a CNN based on the velocity/acceleration spectrograms that finger/wrist movements create. We validated HARCS with the wrist-worn IMU recordings obtained from twenty stroke survivors during their daily life, where the occurrence of finger/wrist movements was labeled using a previously validated algorithm called HAND using magnetic sensing. The daily number of finger/wrist movements identified by HARCS had a strong positive correlation to the daily number identified by HAND (R2 = 0.76, p < 0.001). HARCS was also 75% accurate when we labeled the finger/wrist movements performed by unimpaired participants using optical motion capture. Overall, the ringless sensing of finger/wrist movement occurrence is feasible, although real-world applications may require further accuracy improvements.

Exercise repetition rate measured with simple sensors at home can be used to estimate Upper Extremity Fugl-Meyer score after stroke.

Introduction: It would be valuable if home-based rehabilitation training technologies could automatically assess arm impairment after stroke. Here, we tested whether a simple measure-the repetition rate (or "rep rate") when performing specific exercises as measured with simple sensors-can be used to estimate Upper Extremity Fugl-Meyer (UEFM) score. Methods: 41 individuals with arm impairment after stroke performed 12 sensor-guided exercises under therapist supervision using a commercial sensor system comprised of two pucks that use force and motion sensing to measure the start and end of each exercise repetition. 14 of these participants then used the system at home for three weeks. Results: Using linear regression, UEFM score was well estimated using the rep rate of one forward-reaching exercise from the set of 12 exercises (r2 = 0.75); this exercise required participants to alternately tap pucks spaced about 20 cm apart (one proximal, one distal) on a table in front of them. UEFM score was even better predicted using an exponential model and forward-reaching rep rate (Leave One Out Cross Validation (LOOCV) r2 = 0.83). We also tested the ability of a nonlinear, multivariate model (a regression tree) to predict UEFM, but such a model did not improve prediction (LOOCV r2 = 0.72). However, the optimal decision tree also used the forward-reaching task along with a pinch grip task to subdivide more and less impaired patients in a way consistent with clinical intuition. At home, rep rate for the forward-reaching exercise well predicted UEFM score using an exponential model (LOOCV r2 = 0.69), but only after we re-estimated coefficients using the home data. Discussion: These results show how a simple measure-exercise rep rate measured with simple sensors-can be used to infer an arm impairment score and suggest that prediction models should be tuned separately for the clinic and home environments.

Optimized Home Rehabilitation Technology Reduces Upper Extremity Impairment Compared to a Conventional Home Exercise Program: A Randomized, Controlled, Single-Blind Trial in Subacute Stroke.

BACKGROUND: Upper extremity (UE) stroke rehabilitation requires patients to perform exercises at home, yet patients show limited benefit from paper-based home exercise programs. OBJECTIVE: To compare the effectiveness of 2 home exercise programs for reducing UE impairment: a paper-based approach and a sensorized exercise system that incorporates recommended design features for home rehabilitation technology. METHODS: In this single-blind, randomized controlled trial, 27 participants in the subacute phase of stroke were assigned to the sensorized exercise (n = 14) or conventional therapy group (n = 13), though 2 participants in the conventional therapy group were lost to follow-up. Participants were instructed to perform self-guided movement training at home for at least 3 hours/week for 3 consecutive weeks. The sensorized exercise group used FitMi, a computer game with 2 puck-like sensors that encourages movement intensity and auto-progresses users through 40 exercises. The conventional group used a paper book of exercises. The primary outcome measure was the change in Upper Extremity Fugl-Meyer (UEFM) score from baseline to follow-up. Secondary measures included the Modified Ashworth Scale for spasticity (MAS) and the Visual Analog Pain (VAP) scale. RESULTS: Participants who used FitMi improved by an average of 8.0 ± 4.6 points on the UEFM scale compared to 3.0 ± 6.1 points for the conventional participants, a significant difference (t-test, P = .029). FitMi participants exhibited no significant changes in UE MAS or VAP scores. CONCLUSIONS: A sensor-based exercise system incorporating a suite of recommended design features significantly and safely reduced UE impairment compared to a paper-based, home exercise program. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT03503617.

Targeting neuroplasticity to improve motor recovery after stroke: an artificial neural network model.

After a neurological injury, people develop abnormal patterns of neural activity that limit motor recovery. Traditional rehabilitation, which concentrates on practicing impaired skills, is seldom fully effective. New targeted neuroplasticity protocols interact with the central nervous system to induce beneficial plasticity in key sites and thereby enable wider beneficial plasticity. They can complement traditional therapy and enhance recovery. However, their development and validation is difficult because many different targeted neuroplasticity protocols are conceivable, and evaluating even one of them is lengthy, laborious, and expensive. Computational models can address this problem by triaging numerous candidate protocols rapidly and effectively. Animal and human empirical testing can then concentrate on the most promising ones. Here, we simulate a neural network of corticospinal neurons that control motoneurons eliciting unilateral finger extension. We use this network to (i) study the mechanisms and patterns of cortical reorganization after a stroke; and (ii) identify and parameterize a targeted neuroplasticity protocol that improves recovery of extension torque. After a simulated stroke, standard training produced abnormal bilateral cortical activation and suboptimal torque recovery. To enhance recovery, we interdigitated standard training with trials in which the network was given feedback only from a targeted population of sub-optimized neurons. Targeting neurons in secondary motor areas on ∼20% of the total trials restored lateralized cortical activation and improved recovery of extension torque. The results illuminate mechanisms underlying suboptimal cortical activity post-stroke; they enable the identification and parameterization of the most promising targeted neuroplasticity protocols. By providing initial guidance, computational models could facilitate and accelerate the realization of new therapies that improve motor recovery.

Feasibility of home hand rehabilitation using musicglove after chronic spinal cord injury.

STUDY DESIGN: Randomized, controlled single-blind cross over study. This study was registered on ClinicalTrials.gov (NCT02473614). OBJECTIVES: Examine usership patterns and feasibility of MusicGlove for at home hand rehabilitation therapy following chronic spinal cord injury. SETTING: Homes of participants. METHODS: Ten participants with chronic spinal cord injury completed two baseline assessments of hand function. After a stable baseline was determined all participants were randomized into two groups: Experimental and Control. Each group was given a recommended therapy dosage. Following this participants switched interventions. RESULTS: On average participants had higher levels of compliance (6.1 ± 3.5 h.), and completed more grips (15,760 ± 9,590 grips) compared to participants in previous stroke studies using the same device. Participants modulated game parameters in a manner consistent with optimal challenge principles from motor learning theory. Participants in the experimental group increased their prehension ability (1 ± 1.4 MusicGlove, 0.2 ± 0.5 Control) and performance (1.4 ± 2.2 MusicGlove, 0.4 ± 0.55 Control) on the Graded and Redefined Assessment of Strength, Sensibility, and Prehension subtests. Increases in performance on the Box and Blocks Test also favored the experimental group compared to the conventional group at the end of therapy (4.2 ± 5.9, -1.0 ± 3.4 respectively). CONCLUSIONS: MusicGlove is a feasible option for hand therapy in the home-setting for individuals with chronic SCI. Participants completed nearly twice as many gripping movements compared to individuals from the sub-acute and chronic stroke populations, and a number far greater than the number of movements typically achieved during traditional rehabilitation.

Providing Real-Time Wearable Feedback to Increase Hand Use after Stroke: A Randomized, Controlled Trial.

After stroke, many people substantially reduce use of their impaired hand in daily life, even if they retain even a moderate level of functional hand ability. Here, we tested whether providing real-time, wearable feedback on the number of achieved hand movements, along with a daily goal, can help people increase hand use intensity. Twenty participants with chronic stroke wore the Manumeter, a novel magnetic wristwatch/ring system that counts finger and wrist movements. We randomized them to wear the device for three weeks with (feedback group) or without (control group) real-time hand count feedback and a daily goal. Participants in the control group used the device as a wristwatch, but it still counted hand movements. We found that the feedback group wore the Manumeter significantly longer (11.2 ± 1.3 h/day) compared to the control group (10.1 ± 1.1 h/day). The feedback group also significantly increased their hand counts over time (p = 0.012, slope = 9.0 hand counts/hour per day, which amounted to ~2000 additional counts per day by study end), while the control group did not (p-value = 0.059; slope = 4.87 hand counts/hour per day). There were no significant differences between groups in any clinical measures of hand movement ability that we measured before and after the feedback period, although several of these measures improved over time. Finally, we confirmed that the previously reported threshold relationship between hand functional capacity and daily use was stable over three weeks, even in the presence of feedback, and established the minimal detectable change for hand count intensity, which is about 30% of average daily intensity. These results suggest that disuse of the hand after stroke is temporarily modifiable with wearable feedback, but do not support that a 3-week intervention of wearable hand count feedback provides enduring therapeutic gains.

A Dynamic Wheelchair Armrest for Promoting Arm Exercise and Mobility After Stroke.

Arm movement recovery after stroke can improve with sufficient exercise. However, rehabilitation therapy sessions are typically not enough. To address the need for effective methods of increasing arm exercise outside therapy sessions we developed a novel armrest, called Boost. It easily attaches to a standard manual wheelchair just like a conventional armrest and enables users to exercise their arm in a linear forward-back motion. This paper provides a detailed design description of Boost, the biomechanical analysis method to evaluate the joint torques required to operate it, and the results of pilot testing with five stroke patients. Biomechanics results show the required shoulder flexion and elbow extension torques range from -25% to +36% of the torques required to propel a standard pushrim wheelchair, depending on the direction of applied force. In pilot testing, all five participants were able to exercise the arm with Boost in stationary mode (with lower physical demand). Three achieved overground ambulation (with higher physical demand) exceeding 2 m/s after 2-5 practice trials; two of these could not propel their wheelchair with the pushrim. This simple to use, dynamic armrest provides people with hemiparesis a way to access repetitive arm exercise outside of therapy sessions, independently right in their wheelchair. Significantly, Boost removes the requirements to reach, grip, and release the pushrim to propel a wheelchair, an action many individuals with stroke cannot complete.

Using Large-Scale Sensor Data to Test Factors Predictive of Perseverance in Home Movement Rehabilitation: Optimal Challenge and Steady Engagement.

Persevering with home rehabilitation exercise is a struggle for millions of people in the US each year. A key factor that may influence motivation to engage with rehabilitation exercise is the challenge level of the assigned exercises, but this hypothesis is currently supported only by subjective, self-report. Here, we studied the relationship between challenge level and perseverance using long-term, self-determined exercise patterns of a large number of individuals (N = 2,581) engaging in home rehabilitation with a sensor-based exercise system without formal supervision. FitMi is comprised of two puck-like sensors and a library of 40 gamified exercises for the hands, arms, trunk, and legs that are designed for people recovering from a stroke. We found that individuals showed the greatest perseverance with the system over a 2-month period if they had (1) a moderate level of motor impairment and (2) high but not perfect success during the 1st week at completing the exercise game. Further, a steady usage pattern (vs. accelerating or decelerating use) was associated with more overall exercise, and declines in exercise amount over time were associated with exponentially declining session initiation probability rather than decreasing amounts of exercise once a session was initiated. These findings confirm that an optimized challenge level and regular initiation of exercise sessions predict achievement of a greater amount of overall rehabilitation exercise in a group of users of commercial home rehabilitation technology and suggest how home rehabilitation programs and exercise technologies can be optimized to promote perseverance.

Measuring Movement Quality of the Stroke-Impaired Upper Extremity with a Wearable Sensor: Toward a Smoothness Metric for Home Rehabilitation Exercise Programs.

Remote patient monitoring systems show promise for assisting stroke patients in home exercise programs. While these systems typically measure exercise repetitions in order to monitor compliance, a key goal of therapists is to also monitor movement quality. Here we develop a measure of movement quality - Peak Intensity - that is a measure of movement smoothness that is implementable with a wrist-worn inertial measurement unit (IMU) in the context of performing repetitions of an upper extremity exercise. To calculate Peak Intensity, we assume we have an accurate count of the number of exercise repetitions in an exercise set, then calculate Peak Intensity as the total number of movement peaks from the continuous stream of IMU data generated across the set, divided by the number of repetitions. Using wrist-worn IMU measurements from 19 participants with chronic stroke performing a sample exercise in which they picked up and moved blocks across a divider (i.e. the Box and Blocks Test) we show that Peak Intensity is moderately correlated with a widely used measure of movement quality, the Quality of Movement score of the Motor Activity Log. Peak Intensity is also strongly correlated with a measure of hand function (the BBT score itself), but is more sensitive at greater levels of impairment. Finally, we show Peak Intensity can be validly derived from either wrist acceleration or angular velocity. These results suggest Peak Intensity could serve as an indicator of movement exercise quality for therapists monitoring home rehabilitation, and, potentially, as a means to provide augmented feedback to patients about their exercise quality.

Proprioceptive Gaming: Making Finger Sensation Training Intense and Engaging with the P-Pong Game and PINKIE Robot.

Proprioceptive deficits are common after a stroke and are thought to negatively impact motor learning. Despite this, there is a lack of practical robotic devices for assessing proprioception, as well as few robotic rehabilitation techniques that intensely and engagingly target proprioception. This work first presents the design of a simple robotic device, PINKIE, developed to assess and train finger proprioception. PINKIE uses low-cost actuators and sensors and is fabricated completely from 3D printed, laser cut, and off-the-shelf components. We then describe the design and testing of a gamified proprioceptive training technique, Proprioceptive-Pong (P-Pong), implemented with PINKIE. In P-Pong, players must continuously make game decisions based on sensed index and middle finger positions, as the game robotically moves their fingers instead of screen pixels to express the motion of the ball and paddle. We also report the results of a pilot study in which we investigated the effect of a short bout of P-Pong play on proprioceptive acuity, and quantified user engagement and intrinsic motivation of game play. We randomly assigned 15 unimpaired human participants to play 15 minutes of P-Pong (proprioceptive training group) or a similar but video-only version of Pong (control group). We assessed finger proprioception acuity before and after game play using the Crisscross assessment previously developed by our laboratory, engagement using the User Engagement Scale, and motivation using the Intrinsic Motivation Inventory survey. Following game play, there was a significant improvement in proprioceptive acuity (2.2 ± 2.6 SD mm, p = 0.023) in the proprioceptive training group but not the control group (0.5 ± 0.9 SD mm, p = 0.101). Participants rated P-Pong highly on all survey subscales, and as highly as visual Pong, except in the Perceived Usability and Competence subscales, a finding we discuss. To our knowledge, this work presents the first computer gaming approach for providing intense and engaging finger proprioception training, by splitting the feedback of game elements between the visual and proprioceptive senses. The pilot experiment indicates that the human sensory motor system has the ability to at least temporarily improve proprioception acuity with such game-based training.

A Pilot Study of a Sensor Enhanced Activity Management System for Promoting Home Rehabilitation Exercise Performed during the COVID-19 Pandemic: Therapist Experience, Reimbursement, and Recommendations for Implementation.

Adherence to home exercise programs (HEPs) during physical rehabilitation is usually unmonitored and is thought to be low from self-reports. This article describes exploratory implementation of a Sensor Enhanced Activity Management (SEAM) system that combines HEP management software with a movement sensor for monitoring and motivating HEP adherence. The article also presents results from attempting to gain reimbursement for home use of the system with therapist oversight using Remote Physiologic Monitoring (RPM) codes. Four therapists used the system in their regular practice during the first six months of the COVID-19 pandemic. Therapists filled out surveys, kept notes, and participated in interviews. Billing and reimbursement data were obtained from the treatment facility. Exercise data from the SEAM system were used to understand HEP adherence. Patients were active for a mean of 40% (26% SD) of prescribed days and completed a mean of 25% (25% SD) of prescribed exercises. The therapists billed 23 RPM codes (USD 2353), and payers reimbursed eight of those instances (USD 649.21). The therapists reported that remote monitoring and the use of a physical movement sensor was motivating to their patients and increased adherence. Sustained technical support for therapists will likely improve implementation of new remote monitoring and treatment systems. RPM codes may enable reimbursement for review and program management activities, but, despite COVID-19 CMS waivers, organizations may have more success if these services are billed under supervision of a physician.

A day in the life: a qualitative study of clinical decision-making and uptake of neurorehabilitation technology.

BACKGROUND: Neurorehabilitation engineering faces numerous challenges to translating new technologies, but it is unclear which of these challenges are most limiting. Our aim is to improve understanding of rehabilitation therapists' real-time decision-making processes on the use of rehabilitation technology (RT) in clinical treatment. METHODS: We used a phenomenological qualitative approach, in which three OTs and two PTs employed at a major, technology-encouraging rehabilitation hospital wrote vignettes from a written prompt describing their RT use decisions during treatment sessions with nine patients (4 with stroke, 2 traumatic brain injury, 1 spinal cord injury, 1 with multiple sclerosis). We then coded the vignettes using deductive qualitative analysis from 17 constructs derived from the RT literature and the Consolidated Framework for Implementation Research (CFIR). Data were synthesized using summative content analysis. RESULTS: Of the constructs recorded, the five most prominent are from CFIR determinants of: (i) relative advantage, (ii) personal attributes of the patients, (iii) clinician knowledge and beliefs of the device/intervention, (iv) complexity of the devices including time and setup, and (v) organizational readiness to implement. Therapists characterized candidate RT as having a relative disadvantage compared to conventional treatment due to lack of relevance to functional training. RT design also often failed to consider the multi-faceted personal attributes of the patients, including diagnoses, goals, and physical and cognitive limitations. Clinicians' comfort with RT was increased by their previous training but was decreased by the perceived complexity of RT. Finally, therapists have limited time to gather, setup, and use RT. CONCLUSIONS: Despite decades of design work aimed at creating clinically useful RT, many lack compatibility with clinical translation needs in inpatient neurologic rehabilitation. New RT continue to impede the immediacy, versatility, and functionality of hands-on therapy mediated treatment with simple everyday objects.

Using a bimanual lever-driven wheelchair for arm movement practice early after stroke: A pilot, randomized, controlled, single-blind trial.

OBJECTIVE: Many patients with subacute stroke rely on the nonparetic arm and leg to propel manual wheelchairs. We designed a bimanual, lever-driven wheelchair (LARA) to promote overground mobility and hemiparetic arm exercise. This study measured the feasibility of using LARA to increase arm movement, achieve mobility, and improve arm motor recovery (clinicaltrials.gov/ct2/show/NCT02830893). DESIGN: Randomized, assessor-blind, controlled trial. SETTING: Two inpatient rehabilitation facilities. SUBJECTS: Nineteen patients with subacute stroke (1 week to 2 months post-stroke) received 30 minutes extra arm movement practice daily, while admitted to inpatient rehabilitation (n = 10) or before enrollment in outpatient therapy (n = 9). INTERVENTIONS: Patients were randomized to train with the LARA wheelchair (n = 11) or conventional exercises with a rehabilitation therapist (n = 8). MAIN MEASURES: Number of arm movements per training session; overground speed; Upper Extremity Fugl-Meyer score at three-month follow-up. RESULTS: Participants who trained with LARA completed 254 (median) arm movements with the paretic arm each session. For three participants, LARA enabled wheelchair mobility at practical indoor speeds (0.15-0.30 m/s). Fugl-Meyer score increased 19 ± 13 points for patients who trained with LARA compared to 14 ± 7 points with conventional exercises (P = 0.32). Secondary measures including shoulder pain and increased tone did not differ between groups. Mixed model analysis found significant interaction between LARA training and treatment duration (P = 0.037), informing power analysis for future investigation. CONCLUSIONS: Practising arm movement with a lever-driven wheelchair is a feasible method for increasing arm movement early after stroke. It enabled wheelchair mobility for a subset of patients and shows potential for improving arm motor recovery.

Magnetically Counting Hand Movements: Validation of a Calibration-Free Algorithm and Application to Testing the Threshold Hypothesis of Real-World Hand Use after Stroke.

There are few wearable sensors suitable for daily monitoring of wrist and finger movements for hand-related healthcare applications. Here, we describe the development and validation of a novel algorithm for magnetically counting hand movements. We implemented the algorithm on a wristband that senses magnetic field changes produced by movement of a magnetic ring worn on the finger (the "Manumeter"). The "HAND" (Hand Activity estimated by Nonlinear Detection) algorithm assigns a "HAND count" by thresholding the real-time change in magnetic field created by wrist and/or finger movement. We optimized thresholds to achieve a HAND count accuracy of ~85% without requiring subject-specific calibration. Then, we validated the algorithm in a dexterity-impaired population by showing that HAND counts strongly correlate with clinical assessments of upper extremity (UE) function after stroke. Finally, we used HAND counts to test a recent hypothesis in stroke rehabilitation that real-world UE hand use increases only for stroke survivors who achieve a threshold level of UE functional capability. For 29 stroke survivors, HAND counts measured at home did not increase until the participants' Box and Blocks Test scores exceeded ~50% normal. These results show that a threshold-based magnetometry approach can non-obtrusively quantify hand movements without calibration and also verify a key concept of real-world hand use after stroke.