Exploring the Role of Accelerometers in the Measurement of Real World Upper-Limb Use After Stroke

Wearable-Based Kinematic Analysis of Upper-Limb Movements During Daily Activities Could Provide Insights into Stroke Survivors' Motor Ability

BACKGROUND

Frequent and objective monitoring of motor recovery progression holds significant importance in stroke rehabilitation. Despite extensive studies on wearable solutions in this context, the focus has been predominantly on evaluating limb activity. This study aims to address this limitation by delving into a novel measure of wrist kinematics more intricately related to patients' motor capacity.

OBJECTIVE

To explore a new wearable-based approach for objectively and reliably assessing upper-limb motor ability in stroke survivors using a single inertial sensor placed on the stroke-affected wrist.

METHODS

Seventeen stroke survivors performed a series of daily activities within a simulated home setting while wearing a six-axis inertial measurement unit on the wrist affected by stroke. Inertial data during point-to-point upper-limb movements were decomposed into movement segments, from which various kinematic variables were derived. A data-driven approach was then employed to identify a kinematic variable demonstrating robust internal reliability, construct validity, and convergent validity.

RESULTS

We have identified a key kinematic variable, namely the 90th percentile of movement segment distance during point-to-point movements. This variable exhibited robust reliability (intra-class correlation coefficient of .93) and strong correlations with established clinical measures of motor capacity (Pearson's correlation coefficients of .81 with the Fugl-Meyer Assessment for Upper-Extremity; .77 with the Functional Ability component of the Wolf Motor Function Test; and -.68 with the Performance Time component of the Wolf Motor Function Test).

CONCLUSIONS

The findings underscore the potential for continuous, objective, and convenient monitoring of stroke survivors' motor progression throughout rehabilitation.

A Novel, Wearable Inertial Measurement Unit for Stroke Survivors: Validity, Acceptability, and Usability

OBJECTIVE

To establish the concurrent validity, acceptability, and sensor optimization of a consumer-grade, wearable, multi-sensor system to capture quantity and quality metrics of mobility and upper limb movements in stroke survivors.

DESIGN

Single-session, cross-sectional.

SETTING

Clinical research laboratory.

PARTICIPANTS

Thirty chronic stroke survivors (age 57 (10) years; 33% female) with mild to severe motor impairments participated.

INTERVENTIONS

Not Applicable.

MAIN OUTCOME MEASURES

Participants donned 5 sensors and performed standardized assessments of mobility and upper limb (UL) movement. True/false, positive/negative time in active movement for the UL were calculated and compared to criterion-standards using an accuracy rate. Bland-Altman plots and linear regression models were used to establish concurrent validity of UL movement counts, step counts, and stance time symmetry of MiGo against established criterion-standard measures. Acceptability and sensor optimization were assessed through an end-user survey and decision matrix.

RESULTS

Mobility metrics showed excellent association with criterion-standards for step counts (video: r=0.988, P<.001, IMU: r=0.921, P<.001) and stance-time symmetry (r=0.722, P<.001). In the UL, movement counts showed excellent to good agreement (paretic: r=0.849, P<.001, nonparetic: r=0.672, P<.001). Accuracy of active movement time was 85.2% (paretic) and 88.0% (nonparetic) UL. Most participants (63.3%) had difficulty donning/doffing the sensors. Acceptability was high (4.2/5).

CONCLUSIONS

The sensors demonstrated excellent concurrent validity for mobility metrics and UL movements of stroke survivors. Acceptability of the system was high, but alternative wristbands should be considered.

Filtering walking actigraphy data in children with unilateral cerebral palsy: A preliminary study

This study aimed to determine whether filtering out walking-related actigraphy data improves the reliability and accuracy of real-world upper extremity activity assessment in children with unilateral cerebral palsy. Twenty-two children aged 4-12 years diagnosed with unilateral cerebral palsy were included in this study, which was drawn from a two-phase randomized controlled trial conducted from July 2021 to December 2022. Data were collected from a tertiary hospital in Seoul, Republic of Korea. Participants were monitored using tri-axial accelerometers on both wrists across three time points (namely, T0, T1, and T2) over 3 days; interventions were used between each time point. Concurrently, an in-laboratory study focusing on walking and bimanual tasks was conducted with four participants. Data filtration resulted in a reduction of 8.20% in total data entry. With respect to reliability assessment, the intra-class correlation coefficients indicated enhanced consistency after filtration, with increased values for both the affected and less-affected sides. Before filtration, the magnitude counts for both sides showed varying tendencies, depending on the time points; however, they presented a consistent and stable trend after filtration. The findings of this research underscore the importance of accurately interpreting actigraphy measurements in children with unilateral cerebral palsy for targeted upper limb intervention by filtering walking-induced data.

Utility and usability of a wearable system and progressive-challenge cued exercise program for encouraging use of the more involved arm at-home after stroke-a feasibility study with case reports

BACKGROUND

Understanding the role of adherence to home exercise programs for survivors of stroke is critical to ensure patients perform prescribed exercises and maximize effectiveness of recovery.

METHODS

Survivors of hemiparetic stroke with impaired motor function were recruited into a 7-day study designed to test the utility and usability of a low-cost wearable system and progressive-challenge cued exercise program for encouraging graded-challenge exercise at-home. The wearable system comprised two wrist-worn MetaMotionR+ activity monitors and a custom smartphone app. The progressive-challenge cued exercise program included high-intensity activities (one repetition every 30 s) dosed at 1.5 h per day, embedded within 8 h of passive activity monitoring per day. Utility was assessed using measures of system uptime and cue response rate. Usability and user experience were assessed using well-validated quantitative surveys of system usability and user experience. Self-efficacy was assessed at the end of each day on a visual analog scale that ranged from 0 to 100.

RESULTS

The system and exercise program had objective utility: system uptime was 92 ± 6.9% of intended hours and the rate of successful cue delivery was 99 ± 2.7%. The system and program also were effective in motivating cued exercise: activity was detected within 5-s of the cue 98 ± 3.1% of the time. As shown via two case studies, accelerometry data can accurately reflect graded-challenge exercise instructions and reveal differentiable activity levels across exercise stages. User experience surveys indicated positive overall usability in the home settings, strong levels of personal motivation to use the system, and high degrees of satisfaction with the devices and provided training. Self-efficacy assessments indicated a strong perception of proficiency across participants (95 ± 5.0).

CONCLUSIONS

This study demonstrates that a low-cost wearable system providing frequent haptic cues to encourage graded-challenge exercise after stroke can have utility and can provide an overall positive user experience in home settings. The study also demonstrates how combining a graded exercise program with all-day activity monitoring can provide insight into the potential for wearable systems to assess adherence to-and effectiveness of-home-based exercise programs on an individualized basis.

Perspectives and expectations of stroke survivors using egocentric cameras for monitoring hand function at home: a mixed methods study

PURPOSE

Most stroke survivors have remaining upper limb impairment six months after stroke and require additional rehabilitation and help from family members to enhance their performance of daily activities. First-person (egocentric) video has been proposed to capture the activities of daily living (ADLs) of stroke survivors in order to assess their hand function at home. This study explored the experiences and expectations of stroke survivors regarding the use of egocentric cameras in daily life for rehabilitation applications.

METHODS

Twenty-one chronic stroke survivors recruited for the study were asked to record three sessions of 1.5 h of video of their ADLs at home over two weeks. Their experiences and expectations after completing the recordings were discussed using a structured questionnaire and a semi-structured interview. The questionnaire and interview data were analysed using descriptive statistics and content analysis, respectively. The results were further integrated using a mixed methods analysis for mutual explanation and elaboration.

RESULTS

The themes generated were Camera Usability, Privacy Concerns Related to Home Recordings, Future Use of the Camera in Public, and Information Usefulness. The participants perceived that the camera was easy to use, the information obtained from the recordings was beneficial, and no major concerns about recording at home. A discreet camera and a solution to privacy issues were prerequisites to recording tasks in public.

CONCLUSIONS

There was high acceptance among stroke survivors regarding the use of wearable cameras for rehabilitation purposes in the future. Concerns to be managed include discomfort, self-consciousness, and the privacy of others.Implications for rehabilitationThe egocentric camera was easy for the stroke survivors to use at home. However, they expressed a preference for cameras to be less noticeable and lighter in the future to minimize self-consciousness and discomfort.Expectations for future use of an egocentric camera for upper limb rehabilitation at home from the perspectives of stroke survivors included receiving feedback on their hand function in daily life and guidance on how to improve function.Privacy concerns of stroke survivors regarding recording activities of daily living were mostly avoidable by planning in advance. However, some personal hygiene tasks and virtual meetings were recorded by accident. A checklist of common activities that may raise privacy issues can be provided along with the camera to serve as a reminder to avoid these issues.

The feasibility of the adapted H-GRASP program for perceived and actual daily-life upper limb activity in the chronic phase post-stroke

(Purpose: Assessing feasibility and initial impact of the Home-Graded Repetitive Arm Supplementary Program combined with in-home accelerometer-based feedback (AH-GRASP) on perceived and actual daily-life upper limb (UL) activity in stroke survivors during the chronic phase with good UL motor function but low perceived daily-life activity. Material and methods: A 4-week intervention program (4 contact hours, 48 h self-practice) encompassing task-oriented training, behavioral techniques, phone-based support, monitoring, and weekly feedback sessions using wrist-worn accelerometery was implemented using a pre-post double baseline repeated measures design. Feasibility, clinical assessments, patient-reported outcomes, and accelerometer data were investigated. Results: Of the 34 individuals approached, nineteen were included (recruitment rate 56%). Two dropped out, one due to increased UL pain (retention rate 89%). Seven (41%) achieved the prescribed exercise target (120 min/day, six days/week). Positive patient experiences and improvements in UL capacity, self-efficacy, and contribution of the affected UL to overall activity (p < 0.05, small to large effect sizes) were observed. Additionally, seven participants (41%) surpassed the minimal clinically important difference in perceived UL activity.Conclusions: A home-based UL exercise program with accelerometer-based feedback holds promise for enhancing perceived and actual daily-life UL activity for our subgroup of chronic stroke survivors.

Optimizing Epoch Length and Activity Count Threshold Parameters in Accelerometry: Enhancing Upper Extremity Use Quantification in Cerebral Palsy

Various accelerometry protocols have been used to quantify upper extremity (UE) activity, encompassing diverse epoch lengths and thresholding methods. However, there is no consensus on the most effective approach. The aim of this study was to delineate the optimal parameters for analyzing accelerometry data to quantify UE use in individuals with unilateral cerebral palsy (CP).

METHODS

A group of adults with CP (n = 15) participated in six activities of daily living, while a group of children with CP (n = 14) underwent the Assisting Hand Assessment. Both groups performed the activities while wearing ActiGraph GT9X-BT devices on each wrist, with concurrent video recording. Use ratio (UR) derived from accelerometry and video analysis and accelerometer data were compared for different epoch lengths (1, 1.5, and 2 s) and activity count (AC) thresholds (between 2 and 150).

RESULTS

In adults, results are comparable across epoch lengths, with the best AC thresholds being ≥ 100. In children, results are similar across epoch lengths of 1 and 1.5 (optimal AC threshold = 50), while the optimal threshold is higher with an epoch length of 2 (AC = 75).

CONCLUSIONS

The combination of epoch length and AC thresholds should be chosen carefully as both influence the validity of the quantification of UE use.

Detection and Assessment of Point-to-Point Movements During Functional Activities Using Deep Learning and Kinematic Analyses of the Stroke-Affected Wrist

Stoke is a leading cause of long-term disability, including upper-limb hemiparesis. Frequent, unobtrusive assessment of naturalistic motor performance could enable clinicians to better assess rehabilitation effectiveness and monitor patients' recovery trajectories. We therefore propose and validate a two-phase data analytic pipeline to estimate upper-limb impairment based on the naturalistic performance of activities of daily living (ADLs). Eighteen stroke survivors were equipped with an inertial sensor on the stroke-affected wrist and performed up to four ADLs in a naturalistic manner. Continuous inertial time series were segmented into sliding windows, and a machine-learned model identified windows containing instances of point-to-point (P2P) movements. Using kinematic features extracted from the detected windows, a subsequent model was used to estimate upper-limb motor impairment, as measured by the Fugl-Meyer Assessment (FMA). Both models were evaluated using leave-one-subject-out cross-validation. The P2P movement detection model had an area under the precision-recall curve of 0.72. FMA estimates had a normalized root mean square error of 18.8% with R2=0.72. These promising results support the potential to develop seamless, ecologically valid measures of real-world motor performance.

A deep learning wearable-based solution for continuous at-home monitoring of upper limb goal-directed movements

Introduction

Monitoring upper limb function is crucial for tracking progress, assessing treatment effectiveness, and identifying potential problems or complications. Hand goal-directed movements (GDMs) are a crucial aspect of daily life, reflecting planned motor commands with hand trajectories towards specific target locations. Previous studies have shown that GDM tasks can detect early changes in upper limb function in neurodegenerative diseases and can be used to track disease progression over time.

Methods

In this study, we used accelerometer data from stroke survivor participants and controls doing activities of daily living to develop an automated deep learning approach to detect GDMs. The model performance for detecting GDM or non-GDM from windowed data achieved an AUC of 0.9, accuracy 0.83, sensitivity 0.81, specificity 0.84 and F1 0.82.

Results

We further validated the utility of detecting GDM by extracting features from GDM periods and using these features to classify whether the measurements are collected from a stroke survivor or a control participant, and to predict the Fugl-Meyer assessment score from stroke survivors.

Discussion

This study presents a promising and reliable tool for monitoring upper limb function in a real-world setting, and assessing biomarkers related to upper limb health in neurological, neuromuscular and muscles disorders.

Case Report: Virtual reality training for phantom limb pain after amputation

Several reports have demonstrated the effectiveness of neurorehabilitation, such as mirror therapy or virtual reality, in treating phantom limb pain (PLP). This case study describes the effect of virtual reality training (VRT) on severe, long-term PLP and upper limb activity on the amputated side in a patient who underwent digit amputation 9 years prior. A woman in her 40 s underwent amputation of 2-5 fingers 9 years prior due to a workplace accident. She experienced persistent pain in the palms of her hand near the amputation sites. A single case design (ABA'B') was applied. Periods A and A' were set as periods without VRT intervention, and Periods B and B' were set as periods with VRT intervention. Periods A, B, A', and B' lasted 4, 10, 8, and 10 weeks, respectively. VRT was a task during which visual stimulation and upper limb movements were linked. The task consisted of catching a rolling ball in the display with a virtual hand, operated with both hands using a controller. VRT was performed once every 2-4 weeks for 30 min. Pain intensity was assessed using the short-form McGill Pain Questionnaire-2. Bilateral upper limb activity was measured continuously for 24 h using a triaxial accelerometer attached to the right and left wrist joints. The pain intensity was 147/220 points during Period A, 128 points during Period B, 93 points during Period A', and 100 points during Period B', showing a gradual decrease. Upper limb activity occurred mainly on the intact side during Periods A and B, whereas the activity on the amputated side increased 2-fold after Period A', and both upper extremities were used equally. Virtual reality training resulted in reduced pain intensity and increased activity in the upper limb. VRT may have induced reintegration of the sensory-motor loop, leading to a decrease in the PLP intensity. The upper limb activity on the amputated side may have also increased with the pain reduction. These results suggest that VRT may be valuable in reducing severe, long-term PLP.

The Role and Importance of Using Sensor-Based Devices in Medical Rehabilitation: A Literature Review on the New Therapeutic Approaches

Due to the growth of sensor technology, more affordable integrated circuits, and connectivity technologies, the usage of wearable equipment and sensing devices for monitoring physical activities, whether for wellness, sports monitoring, or medical rehabilitation, has exploded. The current literature review was performed between October 2022 and February 2023 using PubMed, Web of Science, and Scopus in accordance with P.R.I.S.M.A. criteria. The screening phase resulted in the exclusion of 69 articles that did not fit the themes developed in all subchapters of the study, 41 articles that dealt exclusively with rehabilitation and orthopaedics, 28 articles whose abstracts were not visible, and 10 articles that dealt exclusively with other sensor-based devices and not medical ones; the inclusion phase resulted in the inclusion of 111 articles. Patients who utilise sensor-based devices have several advantages due to rehabilitating a missing component, which marks the accomplishment of a fundamental goal within the rehabilitation program. As technology moves faster and faster forward, the field of medical rehabilitation has to adapt to the time we live in by using technology and intelligent devices. This means changing every part of rehabilitation and finding the most valuable and helpful gadgets that can be used to regain lost functions, keep people healthy, or prevent diseases.

Recognizing hand use and hand role at home after stroke from egocentric video

Hand function is a central determinant of independence after stroke. Measuring hand use in the home environment is necessary to evaluate the impact of new interventions, and calls for novel wearable technologies. Egocentric video can capture hand-object interactions in context, as well as show how more-affected hands are used during bilateral tasks (for stabilization or manipulation). Automated methods are required to extract this information. The objective of this study was to use artificial intelligence-based computer vision to classify hand use and hand role from egocentric videos recorded at home after stroke. Twenty-one stroke survivors participated in the study. A random forest classifier, a SlowFast neural network, and the Hand Object Detector neural network were applied to identify hand use and hand role at home. Leave-One-Subject-Out-Cross-Validation (LOSOCV) was used to evaluate the performance of the three models. Between-group differences of the models were calculated based on the Mathews correlation coefficient (MCC). For hand use detection, the Hand Object Detector had significantly higher performance than the other models. The macro average MCCs using this model in the LOSOCV were 0.50 ± 0.23 for the more-affected hands and 0.58 ± 0.18 for the less-affected hands. Hand role classification had macro average MCCs in the LOSOCV that were close to zero for all models. Using egocentric video to capture the hand use of stroke survivors at home is technically feasible. Pose estimation to track finger movements may be beneficial to classifying hand roles in the future.

Wearable technology to capture arm use of stroke survivors in home and community settings: feasibility and early insights on motor performance

Objective

To establish short-term feasibility and usability of wrist-worn wearable sensors to capture arm/hand activity of stroke survivors and to explore the association between factors related to use of the paretic arm/hand.

Methods

30 chronic stroke survivors were monitored with wrist-worn wearable sensors during 12h/day for a 7-day period. Participants also completed standardized assessments to capture stroke severity, arm motor impairments, self-perceived arm use and self-efficacy. Usability of the wearable sensors was assessed using the adapted System Usability Scale and an exit interview. Associations between motor performance and capacity (arm/hand impairments and activity limitations) were assessed using Spearman's correlations.

Results

Minimal technical issues or lack of adherence to the wearing schedule occurred, with 87.6% of days procuring valid data from both sensors. Average sensor wear time was 12.6 (standard deviation: 0.2) h/day. Three participants experienced discomfort with one of the wristbands and three other participants had unrelated adverse events. There were positive self-reported usability scores (mean: 85.4/100) and high user satisfaction. Significant correlations were observed for measures of motor capacity and self-efficacy with paretic arm use in the home and the community (Spearman's correlation ρs: 0.44-0.71).

Conclusions

This work demonstrates the feasibility and usability of a consumer-grade wearable sensor to capture paretic arm activity outside the laboratory. It provides early insight into stroke survivors' everyday arm use and related factors such as motor capacity and self-efficacy.

Impact

The integration of wearable technologies into clinical practice offers new possibilities to complement in-person clinical assessments and to better understand how each person is moving outside of therapy and throughout the recovery and reintegration phase. Insights gained from monitoring stroke survivors arm/hand use in the home and community is the first step towards informing future research with an emphasis on causal mechanisms with clinical relevance.

Application of Deep Learning Algorithm to Monitor Upper Extremity Task Practice

Upper extremity hemiplegia is a serious problem affecting the lives of many people post-stroke. Motor recovery requires high repetitions and quality of task-specific practice. Sufficient practice cannot be completed during therapy sessions, requiring patients to perform additional task practices at home on their own. Adherence to and quality of these home task practices are often limited, which is likely a factor reducing rehabilitation effectiveness post-stroke. However, home adherence is typically measured by self-reports that are known to be inconsistent with objective measurement. The objective of this study was to develop algorithms to enable the objective identification of task type and quality. Twenty neurotypical participants wore an IMU sensor on the wrist and performed four representative tasks in prescribed fashions that mimicked correct, compensatory, and incomplete movement qualities typically seen in stroke survivors. LSTM classifiers were trained to identify the task being performed and its movement quality. Our models achieved an accuracy of 90.8% for task identification and 84.9%, 81.1%, 58.4%, and 73.2% for movement quality classification for the four tasks for unseen participants. The results warrant further investigation to determine the classification performance for stroke survivors and if quantity and quality feedback from objective monitoring facilitates effective task practice at home, thereby improving motor recovery.

A Sensor-Based Feedback Device Stimulating Daily Life Upper Extremity Activity in Stroke Patients: A Feasibility Study

This study aims to evaluate the feasibility and explore the efficacy of the Arm Activity Tracker (AAT). The AAT is a device based on wrist-worn accelerometers that provides visual and tactile feedback to stimulate daily life upper extremity (UE) activity in stroke patients.

METHODS

A randomised, crossover within-subject study was conducted in sub-acute stroke patients admitted to a rehabilitation centre. Feasibility encompassed (1) adherence: the dropout rate and the number of participants with insufficient AAT data collection; (2) acceptance: the technology acceptance model (range: 7-112) and (3) usability: the system usability scale (range: 0-100). A two-way ANOVA was used to estimate the difference between the baseline, intervention and control conditions for (1) paretic UE activity and (2) UE activity ratio.

RESULTS

Seventeen stroke patients were included. A 29% dropout rate was observed, and two participants had insufficient data collection. Participants who adhered to the study reported good acceptance (median (IQR): 94 (77-111)) and usability (median (IQR): 77.5 (75-78.5)-). We found small to medium effect sizes favouring the intervention condition for paretic UE activity (η²G = 0.07, p = 0.04) and ratio (η²G = 0.11, p = 0.22).

CONCLUSION

Participants who adhered to the study showed good acceptance and usability of the AAT and increased paretic UE activity. Dropouts should be further evaluated, and a sufficiently powered trial should be performed to analyse efficacy.

Perspectives of users for a future interactive wearable system for upper extremity rehabilitation following stroke: a qualitative study

BACKGROUND

Wearable sensor technology can facilitate diagnostics and monitoring of people with upper extremity (UE) paresis after stroke. The purpose of this study is to investigate the perspectives of clinicians, people living with stroke, and their caregivers on an interactive wearable system that detects UE movements and provides feedback.

METHODS

This qualitative study used semi-structured interviews relating to the perspectives of a future interactive wearable system including a wearable sensor to capture UE movement and a user interface to provide feedback as the means of data collection. Ten rehabilitation therapists, 9 people with stroke, and 2 caregivers participated in this study.

RESULTS

Four themes were identified (1) "Everyone is different" highlighted the need for addressing individual user's rehabilitation goal and personal preference; (2) "The wearable system should identify UE and trunk movements" emphasized that in addition to arm, hand, and finger movements, detecting compensatory trunk movements during UE movements is also of interest; (3) "Both quality and amount of movements are necessary to measure" described the parameters related to how well and how much the user is using their affected UE that participants envisioned the system to monitor; (4) "Functional activities should be practiced by the users" outlined UE movements and activities that are of priority in designing the system.

CONCLUSIONS

Narratives from clinicians, people with stroke, and their caregivers offer insight into the design of interactive wearable systems. Future studies examining the experience and acceptability of existing wearable systems from end-users are warranted to guide the adoption of this technology.

Outcomes Associated with a Single Joystick-Operated Ride-on-Toy Navigation Training Incorporated into a Constraint-Induced Movement Therapy Program: A Pilot Feasibility Study

Our research aims to evaluate the utility of joystick-operated ride-on-toys (ROTs) as therapeutic adjuncts to improve upper extremity (UE) function in children with hemiplegic cerebral palsy (HCP). This study assessed changes in affected UE use and function following a three-week ROT navigation training incorporated into an existing constraint-induced movement therapy (CIMT) camp in 11 children (3-14 years old) with HCP. We report changes in scores on the standardized Shriners Hospital Upper Extremity Evaluation (SHUEE) from pretest-to-posttest and changes from early-to-late sessions in percent time spent by the affected arm in: (a) "moderate-to-vigorous activity", "light activity" and "no activity" bouts based on accelerometer data and (b) "independent", "assisted", and "no activity" bouts based on video data. We also explored relationships between standardized measures and training-specific measures of affected UE activity. We found small-to-medium improvements in the SHUEE scores. Between 90 and 100% of children also showed medium-to-large improvements in affected UE activity from early-to-late sessions using accelerometers and small improvements via video-based assessments. Exploratory analyses suggested trends for relationships between pretest-posttest and training-specific objective and subjective measures of arm use and function. Our pilot data suggest that single joystick-operated ROTs may serve as motivating, child-friendly tools that can augment conventional therapies such as CIMT to boost treatment dosing, promote affected UE movement practice during real-world navigation tasks, and ultimately improve functional outcomes in children with HCP.

Comparison of wrist actimetry variables of paretic upper limb use in post stroke patients for ecological monitoring

BACKGROUND

To date, many wrist actimetric variables dedicated to measuring the upper limbs (UL) in post-stroke patients have been developed but very few comparisons have been made between them. The objective of this study was to compare different actimetric variables of the ULs between a stroke and healthy population.

METHODS

Accelerometers were worn continuously for a period of 7 days on both wrists of 19 post-stroke hemiparetic patients as well as 11 healthy subjects. Various wrist actimetry variables were calculated, including the Jerk ratio 50 (JR50, cumulative probability that the Jerk Ratio is between 1 and 2), absolute (FuncUse30) and relative (FuncUseRatio30) amounts of functional use of movements of the ULs with angular amplitude greater than 30°, and absolute (UH) and relative (UseHoursRatio) use hours.

RESULTS

FuncUse30, FuncUseRatio30, UH, UseHoursRatio and JR50 of the paretic UL of stroke patients were significantly lower than in the non-dominant UL of healthy subjects. Comparing the ratio variables in stroke patients, FuncUseRatio30 was significantly lower than UseHoursRatio and JR50, suggesting a more clinically sensitive variable to monitor. In an exploratory analysis, FuncUseRatio tends to decrease with angular range of motion for stroke patients while it remains stable and close to 1 for healthy subjects. UseHoursRatio, FuncUseRatio30 and JR50 show linear correlation with Fugl-Meyer score (FM), with r² equal to 0.53, 0.35 and 0.21, respectively.

CONCLUSION

This study determined that the FuncUseRatio30 variable provides the most sensitive clinical biomarker of paretic UL use in post-stroke patients, and that FuncUseHours-angular range of motion relationship allows the identification of the UL behaviour of each patient. This ecological information on the level of functional use of the paretic UL can be used to improve follow-up and develop patient-specific therapy.

Sensor-Based Rehabilitation in Neurological Diseases: A Bibliometric Analysis of Research Trends

BACKGROUND

As the field of sensor-based rehabilitation continues to expand, it is important to gain a comprehensive understanding of its current research landscape. This study aimed to conduct a bibliometric analysis to identify the most influential authors, institutions, journals, and research areas in this field.

METHODS

A search of the Web of Science Core Collection was performed using keywords related to sensor-based rehabilitation in neurological diseases. The search results were analyzed with CiteSpace software using bibliometric techniques, including co-authorship analysis, citation analysis, and keyword co-occurrence analysis.

RESULTS

Between 2002 and 2022, 1103 papers were published on the topic, with slow growth from 2002 to 2017, followed by a rapid increase from 2018 to 2022. The United States was the most active country, while the Swiss Federal Institute of Technology had the highest number of publications among institutions. Sensors published the most papers. The top keywords included rehabilitation, stroke, and recovery. The clusters of keywords comprised machine learning, specific neurological conditions, and sensor-based rehabilitation technologies.

CONCLUSIONS

This study provides a comprehensive overview of the current state of sensor-based rehabilitation research in neurological diseases, highlighting the most influential authors, journals, and research themes. The findings can help researchers and practitioners to identify emerging trends and opportunities for collaboration and can inform the development of future research directions in this field.

Time-Based and Path-Based Analysis of Upper-Limb Movements during Activities of Daily Living

Patients after stroke need to re-learn functional movements required for independent living throughout the rehabilitation process. In the study, we used a wearable sensory system for monitoring the movement of the upper limbs while performing activities of daily living. We implemented time-based and path-based segmentation of movement trajectories and muscle activity to quantify the activities of the unaffected and the affected upper limbs. While time-based segmentation splits the trajectory in quants of equal duration, path-based segmentation isolates completed movements. We analyzed the hand movement path and forearm muscle activity and introduced a bimanual movement parameter, which enables differentiation between unimanual and bimanual activities. The approach was validated in a study that included a healthy subject and seven patients after stroke with different levels of disabilities. Path-based segmentation provides a more detailed and comprehensive evaluation of upper limb activities, while time-based segmentation is more suitable for real-time assessment and providing feedback to patients. Bimanual movement parameter effectively differentiates between different levels of upper limb involvement and is a clear indicator of the activity of the affected limb relative to the unaffected limb.

Improvement in the Capacity for Activity Versus Improvement in Performance of Activity in Daily Life During Outpatient Rehabilitation

We addressed questions about the potential discrepancy between improvements in activity capacity and improvements in activity performance in daily life. We asked whether this discrepancy is: Common in routine, outpatient care, or an artifact of intervention studies? Unique to upper limb (UL) rehabilitation, or is it seen in walking rehabilitation too? Only seen in persons with stroke, or a broader neurorehabilitation problem?

Accelerometer assessed upper limb activity in people with stroke: a validation study considering ambulatory and non-ambulatory activities

PURPOSE

Accelerometry measurements are a promising method to provide quantitative information of upper limb function in daily life post stroke. Our purpose was to investigate i) the validity of accelerometer-based vector magnitude ratios (VMR) to distinguish upper limb function between individuals post-stroke and healthy controls during ambulatory and non-ambulatory activities and, ii) the association between the VMR and clinical assessment of upper limb function for individuals post-stroke.

METHODS

Forty persons with stroke and 32 healthy controls wore wrist and hip accelerometers while performing three upper limb activities in a clinical setting and during three days in daily living. Clinical assessment of upper limb function was assessed with the Chedoke-McMaster Stroke Assessment measure and ABILHand.

RESULTS

In the clinical setting and daily living, the VMR was significantly lower for individuals post-stroke compared to controls during non-ambulatory activities but not during ambulatory activities. There was a moderate to strong association between VMR and clinical assessment of upper limb function during all conditions, except for walking in the clinical setting.

CONCLUSION

The VMR could be used as a sensitive objective marker to measure upper limb function post-stroke during ambulatory and non-ambulatory daily activities.Implications for rehabilitationAccelerometer-based assessment of upper limb function is a sensitive measure of upper limb function post stroke during different activity domains.Accelerometers-based assessment of arm function can detect differences in arm function outside the clinical setting (daily living) over a prolonged period that are not always identified by clinical assessment or perceived ability.

Envisioning the use of in-situ arm movement data in stroke rehabilitation: Stroke survivors' and occupational therapists' perspectives

BACKGROUND

The key for successful stroke upper-limb rehabilitation includes the personalization of therapeutic interventions based on patients' functional ability and performance level. However, therapists often encounter challenges in supporting personalized rehabilitation due to the lack of information about how stroke survivors use their stroke-affected arm outside the clinic. Wearable technologies have been considered as an effective, objective solution to monitor patients' arm use patterns in their naturalistic environments. However, these technologies have remained a proof of concept and have not been adopted as mainstream therapeutic products, and we lack understanding of how key stakeholders perceive the use of wearable technologies in their practice.

OBJECTIVE

We aim to understand how stroke survivors and therapists perceive and envision the use of wearable sensors and arm activity data in practical settings and how we could design a wearable-based performance monitoring system to better support the needs of the stakeholders.

METHODS

We conducted semi-structured interviews with four stroke survivors and 15 occupational therapists (OTs) based on real-world arm use data that we collected for contextualization. To situate our participants, we leveraged a pair of finger-worn accelerometers to collect stroke survivors' arm use data in real-world settings, which we used to create study probes for stroke survivors and OTs, respectively. The interview data was analyzed using the thematic approach.

RESULTS

Our study unveiled a detailed account of (1) the receptiveness of stroke survivors and OTs for using wearable sensors in clinical practice, (2) OTs' envisioned strategies to utilize patient-generated sensor data in the light of providing patients with personalized therapy programs, and (3) practical challenges and design considerations to address for the accelerated integration of wearable systems into their practice.

CONCLUSIONS

These findings offer promising directions for the design of a wearable solution that supports OTs to develop individually-tailored therapy programs for stroke survivors to improve their affected arm use.

The use of wearable sensors to assess and treat the upper extremity after stroke: a scoping review

PURPOSE

To address the gap in the literature and clarify the expanding role of wearable sensor data in stroke rehabilitation, we summarized the methods for upper extremity (UE) sensor-based assessment and sensor-based treatment.

MATERIALS AND METHODS

The guideline outlined by the preferred reporting items for systematic reviews and meta-analysis extension for scoping reviews was used to complete this scoping review. Information pertaining to participant demographics, sensory information, data collection, data processing, data analysis, and study results were extracted from the studies for analysis and synthesis.

RESULTS

We included 43 articles in the final review. We organized the results into assessment and treatment categories. The included articles used wearable sensors to identify UE functional motion, categorize motor impairment/activity limitation, and quantify real-world use. Wearable sensors were also used to augment UE training by triggering sensory cues or providing instructional feedback about the affected UE.

CONCLUSIONS

Sensors have the potential to greatly expand assessment and treatment beyond traditional clinic-based approaches. This capability could support the quantification of rehabilitation dose, the nuanced assessment of impairment and activity limitation, the characterization of daily UE use patterns in real-world settings, and augment UE training adherence for home-based rehabilitation.IMPLICATIONS FOR REHABILITATIONSensor data have been used to assess UE functional motion, motor impairment/activity limitation, and real-world use.Sensor-assisted treatment approaches are emerging, and may be a promising tool to augment UE adherence in home-based rehabilitation.Wearable sensors may extend our ability to objectively assess UE motion beyond supervised clinical settings, and into home and community settings.

Classification of functional and non-functional arm use by inertial measurement units in individuals with upper limb impairment after stroke

Background: Arm use metrics derived from wrist-mounted movement sensors are widely used to quantify the upper limb performance in real-life conditions of individuals with stroke throughout motor recovery. The calculation of real-world use metrics, such as arm use duration and laterality preferences, relies on accurately identifying functional movements. Hence, classifying upper limb activity into functional and non-functional classes is paramount. Acceleration thresholds are conventionally used to distinguish these classes. However, these methods are challenged by the high inter and intra-individual variability of movement patterns. In this study, we developed and validated a machine learning classifier for this task and compared it to methods using conventional and optimal thresholds. Methods: Individuals after stroke were video-recorded in their home environment performing semi-naturalistic daily tasks while wearing wrist-mounted inertial measurement units. Data were labeled frame-by-frame following the Taxonomy of Functional Upper Limb Motion definitions, excluding whole-body movements, and sequenced into 1-s epochs. Actigraph counts were computed, and an optimal threshold for functional movement was determined by receiver operating characteristic curve analyses on group and individual levels. A logistic regression classifier was trained on the same labels using time and frequency domain features. Performance measures were compared between all classification methods. Results: Video data (6.5 h) of 14 individuals with mild-to-severe upper limb impairment were labeled. Optimal activity count thresholds were ≥20.1 for the affected side and ≥38.6 for the unaffected side and showed high predictive power with an area under the curve (95% CI) of 0.88 (0.87,0.89) and 0.86 (0.85, 0.87), respectively. A classification accuracy of around 80% was equivalent to the optimal threshold and machine learning methods and outperformed the conventional threshold by ∼10%. Optimal thresholds and machine learning methods showed superior specificity (75-82%) to conventional thresholds (58-66%) across unilateral and bilateral activities. Conclusion: This work compares the validity of methods classifying stroke survivors' real-life arm activities measured by wrist-worn sensors excluding whole-body movements. The determined optimal thresholds and machine learning classifiers achieved an equivalent accuracy and higher specificity than conventional thresholds. Our open-sourced classifier or optimal thresholds should be used to specify the intensity and duration of arm use.

ARMIA: A Sensorized Arm Wearable for Motor Rehabilitation

In this paper, we present ARMIA: a sensorized arm wearable that includes a combination of inertial and sEMG sensors to interact with serious games in telerehabilitation setups. This device reduces the cost of robotic assistance technologies to be affordable for end-users at home and at rehabilitation centers. Hardware and acquisition software specifications are described together with potential applications of ARMIA in real-life rehabilitation scenarios. A detailed comparison with similar medical technologies is provided, with a specific focus on wearable devices and virtual and augmented reality approaches. The potential advantages of the proposed device are also described showing that ARMIA could provide similar, if not better, the effectivity of physical therapy as well as giving the possibility of home-based rehabilitation.

Suitability of accelerometry as an objective measure for upper extremity use in stroke patients

Background

Upper limb (UL) paresis is one of the most common stroke consequences and significantly restricts patients in everyday life. Instruments objectively measuring direct arm use in stroke patients are lacking, but might be helpful to understand patients’ impairment. Aiming to examine whether accelerometry is a suitable objective measure for everyday UL use in stroke patients, we conducted a systematic review on the association between accelerometer-derived measurements and clinical scales.

Methods

Articles were systematically searched in PubMed, Scopus, Cochrane Library, PeDro and LIVIVO through December 12^th, 2021, screened for inclusion by AH, and subsequently independently screened by CK and MK. Disagreements were discussed until consensus. We included English and German peer-reviewed articles dealing with the validity of accelerometers as a measurement of UL use in stroke patients and eligible systematic reviews. Studies exclusively using accelerometry as an outcome parameter, book contributions, conference abstracts and case studies were excluded. Data extraction was conducted by AH and confirmed by CK focussing on study type, objective, accelerometer device, sample size, stroke status, assessments conducted, measurement method, wearing time and key results. We analysed all eligible articles regarding the correlation between accelerometry and other clinical assessments and the validity in accordance with the type of accelerometer.

Results

Excluding duplicates, the initial search yielded 477 records. In the 34 eligible studies accelerometers was used with a predominance of tri-axial accelerometery (n = 12) and only few with two-axial application (n = 4). Regarding measures to examine association to accelerometer data different clinical scales were applied depending on the setting, the degree of impairment and/or the status of stroke. Cut-off values to determine correlations varied largely; most significant correlations are reported for the MAL [Range 0.31- 0.84] and the ARAT [Range 0.15–0.79].

Conclusions

Accelerometers can provide reliable data about daily arm use frequency but do not supply information about the movements´ quality and restrictions on everyday activities of stroke patients. Depending on the context, it is advisable to use both, accelerometry and other clinical measures. According to the literature there is currently no accelerometer device most suitable to measure UL activity. High correlations indicate that multi-dimensional accelerometers should be preferred.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12883-022-02743-w.

Determinants of Different Aspects of Upper-Limb Activity after Stroke

We examined factors associated with different aspects of upper-limb (UL) activity in chronic stroke to better understand and improve UL activity in daily life. Three different aspects of UL activity were represented by four sensor measures: (1) contribution to activity according to activity ratio and magnitude ratio, (2) intensity of activity according to bilateral magnitude, and (3) variability of activity according to variation ratio. We combined data from a Belgian and Danish patient cohort (n = 126) and developed four models to determine associated factors for each sensor measure. Results from standard multiple regression show that motor impairment (Fugl−Meyer assessment) accounted for the largest part of the explained variance in all sensor measures (18−61%), with less motor impairment resulting in higher UL activity values (p < 0.001). Higher activity ratio, magnitude ratio, and variation ratio were further explained by having the dominant hand affected (p < 0.007). Bilateral magnitude had the lowest explained variance (adjusted R2 = 0.376), and higher values were further associated with being young and female. As motor impairment and biological aspects accounted for only one- to two-thirds of the variance in UL activity, rehabilitation including behavioral strategies might be important to increase the different aspects of UL activity.

Relationship Between Body-Specific Attention to a Paretic Limb and Real-World Arm Use in Stroke Patients: A Longitudinal Study

Learned nonuse is a major problem in upper limb (UL) rehabilitation after stroke. Among the various factors that contribute to learned nonuse, recent studies have focused on body representation of the paretic limb in the brain. We previously developed a method to measure body-specific attention, as a marker of body representation of the paretic limb and revealed a decline in body-specific attention to the paretic limb in chronic stroke patients by a cross-sectional study. However, longitudinal changes in body-specific attention and paretic arm use in daily life (real-world arm use) from the onset to the chronic phase, and their relationship, remain unknown. Here, in a longitudinal, prospective, observational study, we sought to elucidate the longitudinal changes in body-specific attention to the paretic limb and real-world arm use, and their relationship, by using accelerometers and psychophysical methods, respectively, in 25 patients with subacute stroke. Measurements were taken at baseline (TBL), 2 weeks (T2w), 1 month (T1M), 2 months (T2M), and 6 months (T6M) after enrollment. UL function was measured using the Fugl-Meyer Assessment (FMA) and Action Research Arm Test (ARAT). Real-world arm use was measured using accelerometers on both wrists. Body-specific attention was measured using a visual detection task. The UL function and real-world arm use improved up to T6M. Longitudinal changes in body-specific attention were most remarkable at T1M. Changes in body-specific attention up to T1M correlated positively with changes in real-world arm use up to T6M, and from T1M to T6M, and the latter more strongly correlated with changes in real-world arm use. Changes in real-world arm use up to T2M correlated positively with changes in FMA up to T2M and T6M. No correlation was found between body-specific attention and FMA scores. Thus, these results suggest that improved body-specific attention to the paretic limb during the early phase contributes to increasing long-term real-world arm use and that increased real-world use is associated with the recovery of UL function. Our results may contribute to the development of rehabilitation strategies to enhance adaptive changes in body representation in the brain and increase real-world arm use after stroke.

Accelerometry-Based Metrics to Evaluate the Relative Use of the More Affected Arm during Daily Activities in Adults Living with Cerebral Palsy

Adults living with cerebral palsy (CP) report bimanual and unimanual difficulties that interfere with their participation in activities of daily living (ADL). There is a lack of quantitative methods to assess the impact of these motor dysfunctions on the relative use of each arm. The objective of this study was to evaluate the concurrent and discriminative validity of accelerometry-based metrics when used to assess bimanual and unimanual functions.

METHODS

A group of control subjects and hemiplegic adults living with CP performed six ADL tasks, during which they were wearing an Actigraph GT9X on each wrist and being filmed. Four bimanual and unimanual metrics were calculated from both accelerometry-based and video-based data; these metrics were then compared to one other with an intraclass correlation coefficient (ICC). Some of these metrics were previously validated in other clinical population, while others were novel. The discriminative validity was assessed through comparisons between groups and between tasks.

RESULTS

The concurrent validity was considered as good to excellent (ICC = 0.61-0.97) depending on the experience of the raters. The tasks made it possible to discriminate between groups.

CONCLUSION

The proposed accelerometry-based metrics are a promising tool to evaluate bimanual and unimanual functions in adults living with CP.

A Systematic Review of Wearable Sensors for Monitoring Physical Activity

This article reviews the use of wearable sensors for the monitoring of physical activity (PA) for different purposes, including assessment of gait and balance, prevention and/or detection of falls, recognition of various PAs, conduction and assessment of rehabilitation exercises and monitoring of neurological disease progression. The article provides in-depth information on the retrieved articles and discusses study shortcomings related to demographic factors, i.e., age, gender, healthy participants vs patients, and study conditions. It is well known that motion patterns change with age and the onset of illnesses, and that the risk of falling increases with age. Yet, studies including older persons are rare. Gender distribution was not even provided in several studies, and others included only, or a majority of, men. Another shortcoming is that none of the studies were conducted in real-life conditions. Hence, there is still important work to be done in order to increase the usefulness of wearable sensors in these areas. The article highlights flaws in how studies based on previously collected datasets report on study samples and the data collected, which makes the validity and generalizability of those studies low. Exceptions exist, such as the promising recently reported open dataset FallAllD, wherein a longitudinal study with older adults is ongoing.

Human Motion Tracking Using 3D Image Features with a Long Short-Term Memory Mechanism Model-An Example of Forward Reaching

Human motion tracking is widely applied to rehabilitation tasks, and inertial measurement unit (IMU) sensors are a well-known approach for recording motion behavior. IMU sensors can provide accurate information regarding three-dimensional (3D) human motion. However, IMU sensors must be attached to the body, which can be inconvenient or uncomfortable for users. To alleviate this issue, a visual-based tracking system from two-dimensional (2D) RGB images has been studied extensively in recent years and proven to have a suitable performance for human motion tracking. However, the 2D image system has its limitations. Specifically, human motion consists of spatial changes, and the 3D motion features predicted from the 2D images have limitations. In this study, we propose a deep learning (DL) human motion tracking technology using 3D image features with a deep bidirectional long short-term memory (DBLSTM) mechanism model. The experimental results show that, compared with the traditional 2D image system, the proposed system provides improved human motion tracking ability with RMSE in acceleration less than 0.5 (m/s²) X, Y, and Z directions. These findings suggest that the proposed model is a viable approach for future human motion tracking applications.

Upper Limb Performance in Daily Life Approaches Plateau Around Three to Six Weeks Post-stroke

Background. Wearable sensors allow for direct measurement of upper limb (UL) performance in daily life. Objective. To map the trajectory of UL performance and its relationships to other factors post-stroke. Methods. Participants (n = 67) with first stroke and UL paresis were assessed at 2, 4, 6, 8, 12, 16, 20, and 24 weeks after stroke. Assessments captured UL impairment (Fugl-Meyer), capacity for activity (Action Research Arm Test), and performance of activity in daily life (accelerometer variables of use ratio and hours of paretic limb activity), along with other potential modifying factors. We modeled individual trajectories of change for each measurement level and the moderating effects on UL performance trajectories. Results. Individual trajectories were best fit with a 3-parameter logistic model, capturing the rapid growth early after stroke within the longer data collection period. Plateaus (90% of asymptote) in impairment (bootstrap mean ± SE: 32 ± 4 days post-stroke) preceded those in capacity (41 ± 4 days). Plateau in performance, as measured by the use ratio (24 ± 5 days), tended to precede plateaus in impairment and capacity. Plateau in performance, as measured by hours of paretic activity (41 ± 6 days), occurred at a similar time to that of capacity and slightly lagged impairment. Modifiers of performance trajectories were capacity, concordance, UL rehabilitation, depressive symptomatology, and cognition. Conclusions. Upper limb performance in daily life approached plateau 3 to 6 weeks post-stroke. Individuals with stroke started to achieve a stable pattern of UL use in daily life early, often before neurological impairments and functional capacity started to stabilize.

Clinicians' perceptions of a potential wearable device for capturing upper limb activity post-stroke: a qualitative focus group study

Background

There is growing interest in the use of wearable devices that track upper limb activity after stroke to help determine and motivate the optimal dose of upper limb practice. The purpose of this study was to explore clinicians’ perceptions of a prospective wearable device that captures upper limb activity to assist in the design of devices for use in rehabilitation practice.

Methods

Four focus groups with 18 clinicians (occupational and physical therapists with stroke practice experience from a hospital or private practice setting) were conducted. Data were analyzed thematically.

Results

Our analysis revealed three themes: (1) “Quantity and quality is ideal” emphasized how an ideal device would capture both quantity and quality of movement; (2) “Most useful outside therapy sessions” described how therapists foresaw using the device outside of therapy sessions to monitor homework adherence, provide self-monitoring of use, motivate greater use and provide biofeedback on movement quality; (3) “User-friendly please” advocated for the creation of a device that was easy to use and customizable, which reflected the client-centered nature of their treatment.

Conclusions

Findings from this study suggest that clinicians support the development of wearable devices that capture upper limb activity outside of therapy for individuals with some reach to grasp ability. Devices that are easy to use and capture both quality and quantity may result in greater uptake in the clinical setting. Future studies examining acceptability of wearable devices for tracking upper limb activity from the perspective of individuals with stroke are needed.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12984-021-00927-y.

Daily Life Upper Limb Activity for Patients with Match and Mismatch between Observed Function and Perceived Activity in the Chronic Phase Post Stroke

We investigated actual daily life upper limb (UL) activity in relation to observed UL motor function and perceived UL activity in chronic stroke in order to better understand and improve UL activity in daily life. In 60 patients, we collected (1) observed UL motor function (Fugl-Meyer Assessment (FMA-UE)), (2) perceived UL activity (hand subscale of the Stroke Impact Scale (SIS-Hand)), and (3) daily life UL activity (bilateral wrist-worn accelerometers for 72 h) data. Data were compared between two groups of interest, namely (1) good observed (FMA-UE >50) function and good perceived (SIS-Hand >75) activity (good match, n = 16) and (2) good observed function but low perceived (SIS-Hand ≤75) activity (mismatch, n = 15) with Mann-Whitney U analysis. The mismatch group only differed from the good match group in perceived UL activity (median (Q1-Q3) = 50 (30-70) versus 93 (85-100); p < 0.001). Despite similar observed UL motor function and other clinical characteristics, the affected UL in the mismatch group was less active in daily life compared to the good match group (p = 0.013), and the contribution of the affected UL compared to the unaffected UL for each second of activity (magnitude ratio) was lower (p = 0.022). We conclude that people with chronic stroke with low perceived UL activity indeed tend to use their affected UL less in daily life despite good observed UL motor function.

MEASUREMENT OF LOCAL CONSISTENCY OF THE WHOLE BRAIN AFTER AEROBIC EXERCISE BASED ON MAGNETIC RESONANCE IMAGING

ABSTRACT Introduction: The rapid development of rs-fMRI in recent years can provide new scientific evidence of the plasticity of the child's brain. Objective: To reveal the effect of short-term moderate-intensity aerobic exercise on local consistency of brain function in children at rest, and to provide new evidence for elucidating the relationship between physical exercise and plasticity of children's brain. Methods: Using resting state functional magnetic resonance imaging (rs-fMRI) technology and local consistency (ReHo) analysis method to detect a 30-min short-term moderate-intensity aerobic exercise before and after children's brain function local consistency changes; using the Flanker task measurement Changes in children's executive function before and after exercise. Results: 1) A 30-min short-term moderate-intensity aerobic exercise made the children's bilateral posterior buckle back, left dorsolateral prefrontal lobe, left frontal medial gyrus, bilateral central posterior gyrus, left suboccipital gyrus, and tongue gyrus. 2) A 30-minute short-term moderate-intensity aerobic exercise improves children's executive function. 3) ReHo increases in bilateral posterior buckle gyrus, bilateral central parietal posterior gyrus, and left dorsal lateral prefrontal lobe are significantly associated with improved executive function. Conclusions: Short-term moderate-intensity aerobic exercise can improve brain plasticity and executive function by increasing local consistency of brain function in children at rest. Level of evidence II; Therapeutic studies - investigation of treatment results.

Objective Assessment of Postoperative Morbidity After Breast Cancer Treatments with Wearable Activity Monitors: The "BRACELET" Study

Background

Current validated tools to measure upper limb dysfunction after breast cancer treatment, such as questionnaires, are prone to recall bias and do not enable comparisons between patients. This study aimed to test the feasibility of wearable activity monitors (WAMs) for achieving a continuous, objective assessment of functional recovery by measuring peri-operative physical activity (PA).

Methods

A prospective, single-center, non-randomized, observational study was conducted. Patients undergoing breast and axillary surgery were invited to wear WAMs on both wrists in the peri-operative period and then complete upper limb function (DASH) and quality-of-life (EQ-5D-5L) questionnaires. Statistical analyses were performed to determine the construct validity and concurrent validity of WAMs.

Results

The analysis included 39 patients with a mean age of 55 ± 13.2 years. Regain of function on the surgically treated side was observed to be an increase of arm activity as a percentage of preoperative levels, with the greatest increase observed between the postoperative days 1 and 2. The PA was significantly greater on the side not treated by surgery than on the surgically treated side after week 1 (mean PA, 75.8% vs. 62.3%; p < 0.0005) and week 2 (mean PA, 91.6% vs. 77.4%; p < 0.005). Subgroup analyses showed differences in recovery trends between different surgical procedures. Concurrent validity was demonstrated by a significant negative moderate correlation between the PA and DASH questionnaires (R = −0.506; p < 0.05).

Conclusion

This study demonstrated the feasibility and validity of WAMs to objectively measure postoperative recovery of upper limb function after breast surgery, providing a starting point for personalized rehabilitation through early detection of upper limb physical morbidity.

Supplementary Information

The online version contains supplementary material available at 10.1245/s10434-021-10458-4.

mHealth technologies used to capture walking and arm use behavior in adult stroke survivors: a scoping review beyond measurement properties

PURPOSE

We aimed to provide a critical review of measurement properties of mHealth technologies used for stroke survivors to measure the amount and intensity of functional skills, and to identify facilitators and barriers toward adoption in research and clinical practice.

MATERIALS AND METHODS

Using Arksey and O'Malley's framework, two independent reviewers determined eligibility and performed data extraction. We conducted an online consultation survey exercise with 37 experts.

RESULTS

Sixty-four out of 1380 studies were included. A majority reported on lower limb behavior (n = 32), primarily step count (n = 21). Seventeen studies reported on arm-hand behaviors. Twenty-two studies reported metrics of intensity, 10 reported on energy expenditure. Reliability and validity were the most frequently reported properties, both for commercial and non-commercial devices. Facilitators and barriers included: resource costs, technical aspects, perceived usability, and ecological legitimacy. Two additional categories emerged from the survey: safety and knowledge, attitude, and clinical skill.

CONCLUSIONS

This provides an initial foundation for a field experiencing rapid growth, new opportunities and the promise that mHealth technologies affords for envisioning a better future for stroke survivors. We synthesized findings into a set of recommendations for clinicians and clinician-scientists about how best to choose mHealth technologies for one's individual objective.Implications for RehabilitationRehabilitation professionals are encouraged to consider the measurement properties of those technologies that are used to monitor functional locomotor and object-interaction skills in the stroke survivors they serve.Multi-modal knowledge translation strategies (research synthesis, educational courses or videos, mentorship from experts, etc.) are available to rehabilitation professionals to improve knowledge, attitude, and skills pertaining to mHealth technologies.Consider the selection of commercially available devices that are proven to be valid, reliable, accurate, and responsive to the targeted clinical population.Consider usability and privacy, confidentiality and safety when choosing a specific device or smartphone application.

Use of wrist-worn accelerometers to quantify bilateral upper limb activity and asymmetry under free-living conditions in people with multiple sclerosis

BACKGROUND

Although upper limb (UL) dysfunctions are quite common among people with Multiple Sclerosis (pwMS), there is a scarcity of information about actual UL usage under free-living conditions. The aim of the present study is to quantitatively assess 'real-world' activity time, intensity and possible asymmetry of use among dominant and non-dominant ULs in pwMS.

METHODS

Twenty-eight pwMS (20 women, 8 men, average EDSS 4.3) and 28 age- and sex-matched unaffected individuals were required to wear a tri-axial accelerometer on each wrist 24h/day for 2 weekdays. Raw accelerations were processed to calculate parameters associated with time and intensity of use of UL both when engaged in uni- or bilateral activities.

RESULTS

During the 2-day monitoring period, pwMS were characterized by significantly lower overall activity, they used their dominant limb for a significantly longer time and, while performing bilateral activities, their dominant limb expressed movements of superior intensity in a proportion higher than what was observed in unaffected individuals.

CONCLUSION

The instrumental monitoring of UL activity with two wrist-worn sensors may represent an effective tool for assessing the contribution of each limb to uni- and bilateral movements. Such data can be employed to monitor the progression of UL dysfunctions and the effectiveness of pharmacologic and rehabilitative treatments.

Predicting and Monitoring Upper-Limb Rehabilitation Outcomes Using Clinical and Wearable Sensor Data in Brain Injury Survivors

OBJECTIVE

Rehabilitation specialists have shown considerable interest for the development of models, based on clinical data, to predict the response to rehabilitation interventions in stroke and traumatic brain injury survivors. However, accurate predictions are difficult to obtain due to the variability in patients' response to rehabilitation interventions. This study aimed to investigate the use of wearable technology in combination with clinical data to predict and monitor the recovery process and assess the responsiveness to treatment on an individual basis.

METHODS

Gaussian Process Regression-based algorithms were developed to estimate rehabilitation outcomes (i.e., Functional Ability Scale scores) using either clinical or wearable sensor data or a combination of the two.

RESULTS

The algorithm based on clinical data predicted rehabilitation outcomes with a Pearson's correlation of 0.79 compared to actual clinical scores provided by clinicians but failed to model the variability in responsiveness to the intervention observed across individuals. In contrast, the algorithm based on wearable sensor data generated rehabilitation outcome estimates with a Pearson's correlation of 0.91 and modeled the individual responses to rehabilitation more accurately. Furthermore, we developed a novel approach to combine estimates derived from the clinical data and the sensor data using a constrained linear model. This approach resulted in a Pearson's correlation of 0.94 between estimated and clinician-provided scores.

CONCLUSION

This algorithm could enable the design of patient-specific interventions based on predictions of rehabilitation outcomes relying on clinical and wearable sensor data.

SIGNIFICANCE

This is important in the context of developing precision rehabilitation interventions.

Upper limb movement profiles during spontaneous motion in acute stroke

Objective.The clinical assessment of upper limb hemiparesis in acute stroke involves repeated manual examination of hand movements during instructed tasks. This process is labour-intensive and prone to human error as well as being strenuous for the patient. Wearable motion sensors can automate the process by measuring characteristics of hand activity. Existing work in this direction either uses multiple sensors or complex instructed movements, or analyzes only thequantityof upper limb motion. These methods are obtrusive and strenuous for acute stroke patients and are also sensitive to noise. In this work, we propose to use only two wrist-worn accelerometer sensors to study thequalityof completely spontaneous upper limb motion and investigate correlation with clinical scores for acute stroke care.Approach.The velocity time series estimated from acquired acceleration data during spontaneous motion is decomposed into smaller movement elements. Measures of density, duration and smoothness of these component elements are extracted and their disparity is studied across the two hands.Main results.Spontaneous upper limb motion in acute stroke can be decomposed into movement elements that resemble point-to-point reaching tasks. These elements are smoother and sparser in the normal hand than in the hemiparetic hand, and the amount of smoothness correlates with hemiparetic severity. Features characterizing the disparity of these movement elements between the two hands show statistical significance in differentiating mild-to-moderate and severe hemiparesis. Using data from 67 acute stroke patients, the proposed method can classify the two levels of hemiparetic severity with 85% accuracy. Additionally, compared to activity-based features, the proposed method is robust to the presence of noise in acquired data.Significance.This work demonstrates that the quality of upper limb motion can characterize and identify hemiparesis in stroke survivors. This is clinically significant towards the continuous automated assessment of hemiparesis in acute stroke using minimally intrusive wearable sensors.

A Novel Combination of Accelerometry and Ecological Momentary Assessment for Post-Stroke Paretic Arm/Hand Use: Feasibility and Validity

Use of the paretic arm and hand is a key indicator of recovery and reintegration after stroke. A sound methodology is essential to comprehensively identify the possible factors impacting daily arm/hand use behavior. We combined ecological momentary assessment (EMA), a prompt methodology capturing real-time psycho-contextual factors, with accelerometry to investigate arm/hand behavior in the natural environment. Our aims were to determine (1) feasibility and (2) measurement validity of the combined methodology. We monitored 30 right-dominant, mild-moderately motor impaired chronic stroke survivors over 5 days (6 EMA prompts/day with accelerometers on each wrist). We observed high adherence for accelerometer wearing time (80.3%), EMA prompt response (84.6%), and generally positive user feedback upon exit interview. The customized prompt schedule and the self-triggered prompt option may have improved adherence. There was no evidence of EMA response bias nor immediate measurement reactivity. An unexpected small but significant increase in paretic arm/hand use was observed over days (12–14 min), which may be the accumulated effect of prompting that provided a reminder to choose the paretic limb. Further research that uses this combined methodology is needed to develop targeted interventions that effectively change behavior and enable reintegration post-stroke.

Factors related to daily use of the paretic upper limb in patients with chronic hemiparetic stroke-A retrospective cross-sectional study

AIMS

The present study aimed to determine factors associated with the frequency of paralyzed upper extremity (UE) use in chronic stroke patients with severe UE functional deficiency.

METHODS

We retrospectively reviewed the medical records of 138 consecutive patients, and 117 was analyzed (median age, 55 [range, 18-85] years; median stroke duration, 24.5 [range, 7-302] months) with chronic hemiparetic stroke who were admitted to our hospital for intensive upper extremity rehabilitation. The mean Fugl-Meyer Assessment (FMA) UE score was 28.6. All of them are independent in their activity of daily living (ADL) and without remarkable cognitive deficits. Amount-of-use score of Motor Activity Log-14 (MAL-AOU) was applied as the index of daily use of affected UE. The following parameters were examined as the explanatory variables: demographics, proximal and distal sub-scores of FMA UE, Modified Ashworth Scale (MAS), and sensory function scores in the Stroke Impairment Assessment Set (SIAS).

RESULTS

The median MAL-AOU score was 0.57 [range, 0.28-0.80]. Ordinal regression analysis revealed that FMA proximal, FMA distal, and SIAS sensory function (touch) were associated with AOU score of MAL-14 (Pseudo R-square = 0.460).

CONCLUSION

Not only motor but also sensory function, especially tactile sensation, play a crucial role in the daily use of affected UE in chronic stroke patients with severe UE hemiparesis.

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.

Sensor-based categorization of upper limb performance in daily life of persons with and without neurological upper limb deficits

Background: The use of wearable sensor technology (e. g., accelerometers) for tracking human physical activity have allowed for measurement of actual activity performance of the upper limb (UL) in daily life. Data extracted from accelerometers can be used to quantify multiple variables measuring different aspects of UL performance in one or both limbs. A limitation is that several variables are needed to understand the complexity of UL performance in daily life.

Purpose: To identify categories of UL performance in daily life in adults with and without neurological UL deficits.

Methods: This study analyzed data extracted from bimanual, wrist-worn triaxial accelerometers from adults from three previous cohorts (N = 211), two samples of persons with stroke and one sample from neurologically intact adult controls. Data used in these analyses were UL performance variables calculated from accelerometer data, associated clinical measures, and participant characteristics. A total of twelve cluster solutions (3-, 4-, or 5-clusters based with 12, 9, 7, or 5 input variables) were calculated to systematically evaluate the most parsimonious solution. Quality metrics and principal component analysis of each solution were calculated to arrive at a locally-optimal solution with respect to number of input variables and number of clusters.

Results: Across different numbers of input variables, two principal components consistently explained the most variance. Across the models with differing numbers of UL input performance variables, a 5-cluster solution explained the most overall total variance (79%) and had the best model-fit.

Conclusion: The present study identified 5 categories of UL performance formed from 5 UL performance variables in cohorts with and without neurological UL deficits. Further validation of both the number of UL performance variables and categories will be required on a larger, more heterogeneous sample. Following validation, these categories may be used as outcomes in UL stroke research and implemented into rehabilitation clinical practice.

Generalizability of Hand-Object Interaction Detection in Egocentric Video across Populations with Hand Impairment

Stroke survivors often experience unilateral sensorimotor impairment. The restoration of upper limb function is an important determinant of quality of life after stroke. Wearable technologies that can measure hand function at home are needed to assess the impact of new interventions. Egocentric cameras combined with computer vision algorithms have been proposed as a means to capture hand use in unconstrained environments, and have shown promising results in this application for individuals with cervical spinal cord injury (cSCI). The objective of this study was to examine the generalizability of this approach to individuals who have experienced a stroke. An egocentric camera was used to capture the hand use (hand-object interactions) of 6 stroke survivors performing daily tasks in a home simulation laboratory. The interaction detection classifier previously trained on 9 individuals with cSCI was applied to detect hand use in the stroke survivors. The processing pipeline consisted of hand detection, hand segmentation, feature extraction, and interaction detection. The resulting average F1 scores for affected and unaffected hands were 0.66 ± 0.25 and 0.80 ± 0.15, respectively, indicating that the approach is feasible and has the potential to generalize to stroke survivors. Using stroke-specific training data may further increase the accuracy obtained for the affected hand.

Bilateral capacity is related to bilateral upper limb use after stroke: a study by behavioral maps, accelerometers and perceived amount of use

PURPOSE

This study aimed to assess the following in individuals after stroke: (1) relationship between upper limb (UL) use by direct observation at home with use perceived and measured by accelerometers; (2) complementarity of these three measurements; and (3) relationship between UL bilateral capacity and bilateral use.

MATERIALS AND METHODS

Thirty-one individuals with chronic hemiparesis participated in this cross-sectional study. UL use was assessed using a behavioral map (BM), the Motor Activity Log-Amount of Use (MAL-AOU), and accelerometers, while UL capacity was assessed using the Test d'Evaluation des Membres Supérieurs des Personnes Âgées (TEMPA).

RESULTS

The BM was strongly correlated with perceived use (MAL-AOU, ρ = 0.76) and accelerometer (ρ = 0.70). Bilateral UL use (BM) was moderately (ρ = 0.65) correlated with bilateral MAL-AOU and bilateral use by accelerometers (ρ = 0.62). The BM aided our understanding of how the paretic UL was used. The correlation between bilateral capacity (TEMPA bilateral) and bilateral use (BM) was significant (ρ = 0.49), while that with bilateral MAL-AOU and accelerometer were ρ = 0.68 and ρ = 0.50, respectively.

CONCLUSION

A BM is a valid way to quantify UL use and can complement information assessed regarding perceived use and by accelerometers.Implications for rehabilitationBehavioral maps may be valuable to complement information assessed by perceived UL use and accelerometers.Quantifying bilateral capacity will reflect in a better understanding of actual paretic UL use after stroke.Accelerometers can underestimate the amount of paretic UL use in asymmetrical bilateral tasks.