Validity of body-worn sensor acceleration metrics to index upper extremity function in hemiparetic stroke

A Large Harmonized Upper and Lower Limb Accelerometry Dataset: A Resource for Rehabilitation Scientists

Wearable sensors can measure movement in daily life, an outcome that is salient to patients, and have been critical to accelerating progress in rehabilitation research and practice. However, collecting and processing sensor data is burdensome, leaving many scientists with limited access to such data. To address these challenges, we present a harmonized, wearable sensor dataset that combines 2,885 recording days of sensor data from the upper and lower limbs from eight studies. The dataset includes 790 individuals ages 0 - 90, nearly equal sex proportions (53% male, 47% female), and representation from a range of demographic backgrounds (69.4% White, 24.9% Black, 1.8% Asian) and clinical conditions (46% neurotypical, 31% stroke, 7% Parkinson's disease, 6% orthopedic conditions, and others). The dataset is publicly available and accompanied by open source code and an app that allows for interaction with the data. This dataset will facilitate the use of sensor data to advance rehabilitation research and practice, improve the reproducibility and replicability of wearable sensor studies, and minimize costs and duplicated scientific efforts.

An Algorithm for Activity Recognition and Assessment of Adults Poststroke

IMPORTANCE

Stroke is the leading cause of long-term disability in the United States. Providers have no robust tools to objectively and accurately measure the activity of people with stroke living at home.

OBJECTIVE

To explore the integration of validated upper extremity assessments poststroke within an activity recognition system.

DESIGN

Exploratory descriptive study using data previously collected over 3 mo to report on algorithm testing and assessment integration.

SETTING

Data were collected in the homes of community-dwelling participants.

PARTICIPANTS

Participants were at least 6 mo poststroke, were able to ambulate with or without an assistive device, and self-reported some difficulty using their arm in everyday activities.

OUTCOMES AND MEASURES

The activity detection algorithm's accuracy was determined by comparing its activity labels with manual labels. The algorithm integrated assessment by describing the quality of upper extremity movement, which was determined by reporting extent of reach, mean and maximum speed during movement, and smoothness of movement.

RESULTS

Sixteen participants (9 women, 7 men) took part in this study, with an average age of 63.38 yr (SD = 12.84). The algorithm was highly accurate in correctly identifying activities, with 87% to 95% accuracy depending on the movement. The algorithm was also able to detect the quality of movement for upper extremity movements.

CONCLUSIONS AND RELEVANCE

The algorithm was able to accurately identify in-kitchen activities performed by adults poststroke. Information about the quality of these movements was also successfully calculated. This algorithm has the potential to supplement clinical assessments in treatment planning and outcomes reporting. Plain-Language Summary: This study shows that clinical algorithms have the potential to inform occupational therapy practice by providing clinically relevant data about the in-home activities of adults poststroke. The algorithm accurately identified activities that were performed in the kitchen by adults poststroke. The algorithm also identified the quality of upper extremity movements of people poststroke who were living at home.

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.

Associations Between Coordination and Wearable Sensor Variables Vary by Recording Context but Not Assessment Type

Motor coordination is an important driver of development and improved coordination assessments could facilitate better screening, diagnosis, and intervention for children at risk of developmental disorders. Wearable sensors could provide data that enhance the characterization of coordination and the clinical utility of that data may vary depending on how sensor variables from different recording contexts relate to coordination. We used wearable sensors at the wrists to capture upper-limb movement in 85 children aged 6-12. Sensor variables were extracted from two recording contexts. Structured recordings occurred in the lab during a unilateral throwing task. Unstructured recordings occurred during free-living activity. The objective was to determine the influence of recording context (unstructured versus structured) and assessment type (direct vs. indirect) on the association between sensor variables and coordination. The greatest associations were between six sensor variables from the structured context and the direct measure of coordination. Worse coordination scores were associated with upper-limb movements that had higher peak magnitudes, greater variance, and less smoothness. The associations were consistent across both arms, even though the structured task was unilateral. This finding suggests that wearable sensors could be paired with a simple, structured task to yield clinically informative variables that relate to motor coordination.

Understanding stroke survivors' preferences regarding wearable sensor feedback on functional movement: a mixed-methods study

BACKGROUND

In stroke rehabilitation, wearable technology can be used as an intervention modality by providing timely, meaningful feedback on motor performance. Stroke survivors' preferences may offer a unique perspective on what metrics are intuitive, actionable, and meaningful to change behavior. However, few studies have identified feedback preferences from stroke survivors. This project aims to determine the ease of understanding and movement encouragement of feedback based on wearable sensor data (both arm/hand use and mobility) for stroke survivors and to identify preferences for feedback metrics (mode, content, frequency, and timing).

METHODS

A sample of 30 chronic stroke survivors wore a multi-sensor system in the natural environment over a 1-week monitoring period. The sensor system captured time in active movement of each arm, arm use ratio, step counts and stance time symmetry. Using the data from the monitoring period, participants were presented with a movement report with visual displays of feedback about arm/hand use, step counts and gait symmetry. A survey and qualitative interview were used to assess ease of understanding, actionability and components of feedback that users found most meaningful to drive lasting behavior change.

RESULTS

Arm/hand use and mobility sensor-derived feedback metrics were easy to understand and actionable. The preferred metric to encourage arm/hand use was the hourly arm use bar plot, and similarly the preferred metric to encourage mobility was the hourly steps bar plot, which were each ranked as top choice by 40% of participants. Participants perceived that quantitative (i.e., step counts) and qualitative (i.e., stance time symmetry) mobility metrics provided complementary information. Three main themes emerged from the qualitative analysis: (1) Motivation for behavior change, (2) Real-time feedback based on individual goals, and (3) Value of experienced clinicians for prescription and accountability. Participants stressed the importance of having feedback tailored to their own personalized goals and receiving guidance from clinicians on strategies to progress and increase functional movement behavior in the unsupervised home and community setting.

CONCLUSION

The resulting technology has the potential to integrate engineering and personalized rehabilitation to maximize participation in meaningful life activities outside clinical settings in a less structured environment.

Bimanual Movement Characteristics and Real-World Performance Following Hand-Arm Bimanual Intensive Therapy in Children with Unilateral Cerebral Palsy

The purpose of this study was to quantify characteristics of bimanual movement intensity during 30 h of hand-arm bimanual intensive therapy (HABIT) and bimanual performance (activities and participation) in real-world settings using accelerometers in children with unilateral cerebral palsy (UCP). Twenty-five children with UCP participated in a 30 h HABIT program. Data were collected from bilateral wrist-worn accelerometers during 30 h of HABIT to quantify the movement intensity and three days pre- and post-HABIT to assess real-world performance gains. Movement intensity and performance gains were measured using six standard accelerometer-derived variables. Bimanual capacity (body function and activities) was assessed using standardized hand function tests. We found that accelerometer variables increased significantly during HABIT, indicating increased bimanual symmetry and intensity. Post-HABIT, children demonstrated significant improvements in all accelerometer metrics, reflecting real-world performance gains. Children also achieved significant and clinically relevant changes in hand capacity following HABIT. Therefore, our findings suggest that accelerometers can objectively quantify bimanual movement intensity during HABIT. Moreover, HABIT enhances hand function as well as activities and participation in real-world situations in children with UCP.

Predicting later categories of upper limb activity from earlier clinical assessments following stroke: an exploratory analysis

BACKGROUND

Accelerometers allow for direct measurement of upper limb (UL) activity. Recently, multi-dimensional categories of UL performance have been formed to provide a more complete measure of UL use in daily life. Prediction of motor outcomes after stroke have tremendous clinical utility and a next step is to explore what factors might predict someone's subsequent UL performance category.

PURPOSE

To explore how different machine learning techniques can be used to understand how clinical measures and participant demographics captured early after stroke are associated with the subsequent UL performance categories.

METHODS

This study analyzed data from two time points from a previous cohort (n = 54). Data used was participant characteristics and clinical measures from early after stroke and a previously established category of UL performance at a later post stroke time point. Different machine learning techniques (a single decision tree, bagged trees, and random forests) were used to build predictive models with different input variables. Model performance was quantified with the explanatory power (in-sample accuracy), predictive power (out-of-bag estimate of error), and variable importance.

RESULTS

A total of seven models were built, including one single decision tree, three bagged trees, and three random forests. Measures of UL impairment and capacity were the most important predictors of the subsequent UL performance category, regardless of the machine learning algorithm used. Other non-motor clinical measures emerged as key predictors, while participant demographics predictors (with the exception of age) were generally less important across the models. Models built with the bagging algorithms outperformed the single decision tree for in-sample accuracy (26-30% better classification) but had only modest cross-validation accuracy (48-55% out of bag classification).

CONCLUSIONS

UL clinical measures were the most important predictors of the subsequent UL performance category in this exploratory analysis regardless of the machine learning algorithm used. Interestingly, cognitive and affective measures emerged as important predictors when the number of input variables was expanded. These results reinforce that UL performance, in vivo, is not a simple product of body functions nor the capacity for movement, instead being a complex phenomenon dependent on many physiological and psychological factors. Utilizing machine learning, this exploratory analysis is a productive step toward the prediction of UL performance. Trial registration NA.

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?

A Feasibility Study of Bilateral Wrist Sensors for Measuring Motor Traits in Children With Autism

Direct, quantitative measures of hyperactivity and motor coordination, two motor characteristics associated with impairment in autism, are limited. Wearable sensors can objectively index real-world movement variables that may relate to these behaviors. Here, we explored the feasibility of bilateral wrist accelerometers for measuring upper limb activity in 3-10-year-olds with autism (n = 22; 19 boys, 3 girls; M age = 5.64, SD = 2.73 years) and without autism (n = 26; 15 boys, 11 girls; M age = 6.26, SD = 2.47 years). We investigated the relationships between movement characteristics related to duration, intensity, complexity, and symmetry on the one hand and parent-reported hyperactivity and motor coordination on the other. Participants with and without autism wore the sensors for 12-hour periods. Sensor variables varied by age but not sex, with movement intensity and complexity moderately related to motor coordination. These findings lend preliminary support to wearable sensors as a means of providing ecologically-valid metrics of motor characteristics that impact adaptive function in children with autism.

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.

Music-based intervention drives paretic limb acceleration into intentional movement frequencies in chronic stroke rehabilitation

This study presented a novel kinematic assessment of paretic limb function "online" during the actual therapeutic exercisers rooted within the acceleration domain. Twenty-eight patients at chronic stroke stages participated in an auditory-motor intervention mapping reaching movements of the paretic arm unto surfaces of large digital musical instruments and sound tablets that provided rhythmic entrainment cues and augmented auditory feedback. Patients also wore a tri-axial accelerometer on the paretic limb during the nine-session intervention. The resulting acceleration profiles were extracted and quantified within the frequency domain. Measures of peak power and peak width were leveraged to estimate volitional control and temporal consistency of paretic limb movements, respectively. Clinical assessments included the Wolf Motor Function Test and Fugl-Meyer - Upper Extremity subtest. The results showed that peak power increased significantly from Session 1 to Session 9 within oscillatory frequency ranges associated with intentional movement execution (i.e., 4.5 Hz). Decreases in peak width over time provided additional evidence for improved paretic arm control from a temporal perspective. In addition, Peak width values obtained in Session 1 was significantly correlated with pre-test Fugl-Meyer - Upper Extremity scores. These results highlighted improvements in paretic limb acceleration as an underlying mechanism in stroke motor recovery and shed further light on the utility of accelerometry-based measures of paretic limb control in stroke rehabilitation. The data reported here was obtained from a larger clinical trial: https://clinicaltrials.gov/ct2/show/NCT03246217 ClinicalTrials.gov Identifier: NCT03246217.

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.

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.

Evidence for the Effectiveness of Feedback from Wearable Inertial Sensors during Work-Related Activities: A Scoping Review

Background: Wearable inertial sensor technology (WIST) systems provide feedback, aiming to modify aberrant postures and movements. The literature on the effects of feedback from WIST during work or work-related activities has not been previously summarised. This review examines the effectiveness of feedback on upper body kinematics during work or work-related activities, along with the wearability and a quantification of the kinematics of the related device. Methods: The Cinahl, Cochrane, Embase, Medline, Scopus, Sportdiscus and Google Scholar databases were searched, including reports from January 2005 to July 2021. The included studies were summarised descriptively and the evidence was assessed. Results: Fourteen included studies demonstrated a 'limited' level of evidence supporting posture and/or movement behaviour improvements using WIST feedback, with no improvements in pain. One study assessed wearability and another two investigated comfort. Studies used tri-axial accelerometers or IMU integration (n = 5 studies). Visual and/or vibrotactile feedback was mostly used. Most studies had a risk of bias, lacked detail for methodological reproducibility and displayed inconsistent reporting of sensor technology, with validation provided only in one study. Thus, we have proposed a minimum 'Technology and Design Checklist' for reporting. Conclusions: Our findings suggest that WIST may improve posture, though not pain; however, the quality of the studies limits the strength of this conclusion. Wearability evaluations are needed for the translation of WIST outcomes. Minimum reporting standards for WIST should be followed to ensure methodological reproducibility.

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.

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.

Advances in motion and electromyography based wearable technology for upper extremity function rehabilitation: A review

STUDY DESIGN

Scoping review.

INTRODUCTION

With the recent advances in technologies, interactive wearable technologies including inertial motion sensors and e-textiles are emerging in the field of rehabilitation to monitor and provide feedback and therapy remotely.

PURPOSE OF THE STUDY

This review article focuses on inertial measurement unit motion sensor and e-textiles-based technologies and proposes approaches to augment these interactive wearable technologies.

METHODS

We conducted a comprehensive search of relevant electronic databases (eg, PubMed, the Cumulative Index to Nursing and Allied Health Literature, Embase, PsycINFO, The Cochrane Central Register of Controlled Trial, and the Physiotherapy Evidence Database). The scoping review included all study designs.

RESULTS

Currently, there are a numerous research groups and companies investigating inertial motion sensors and e-textiles-based interactive wearable technologies. However, translation of these technologies to the clinic would need further research to increase ease of use and improve clinical validity of the outcomes of these technologies.

DISCUSSION

The current review discusses the limitations of the interactive wearable technologies such as, limited clinical utility, bulky equipment, difficulty in setting up equipment inertial motion sensors and e-textiles.

CONCLUSION

There is tremendous potential for interactive wearable technologies in rehabilitation. With the evolution of cloud computing, interactive wearable systems can remotely provide intervention and monitor patient progress using models of telerehabilitation. This will revolutionize the delivery of rehabilitation and make rehabilitation more accessible and affordable to millions of individuals.

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.

A Comparative Efficacy Study of Robotic Priming of Bilateral Approach in Stroke Rehabilitation

Background: Stroke survivors can remain impaired in body functions, activity, and participation. A novel rehabilitation regimen is required to obtain scientific evidence and to help clinicians determine effective interventions for stroke. Mirror therapy (MT) and bilateral upper limb training (BULT) are based on the tenet of bilateral movement practice; however, the additional effect of bilateral robotic priming combined with these two therapies is unclear. Objectives: This study examined the effects of two hybrid therapies, robotic priming combined with MT and robotic priming combined with BULT, in stroke survivors. Methodology: The study randomized 31 participants to groups that received robotic priming combined with MT (n = 15) or robotic priming combined with BULT (n = 16). Outcome measures included the Fugl-Meyer Assessment (FMA), the revised Nottingham Sensory Assessment (rNSA), the Chedoke Arm and Hand Activity Inventory (CAHAI), and accelerometer data. Results: Both groups showed statistically significant within-group improvements in most outcome measures. Significant between-group differences and medium-to-large effect sizes were found in favor of the group that received robotic priming combined with MT based on the FMA distal part subscale scores, FMA total scores, and accelerometer data. Conclusion: Robotic priming combined with MT may have beneficial effects for patients in the improvements of overall and distal arm motor impairment as well as affected arm use in real life. Additional follow-up, a larger sample size, and consideration of the effect of lesion location or different levels of cognitive impairment are warranted to validate our findings in future studies. Clinical trial registration: www.ClinicalTrials.gov, identifier NCT03773653.

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.

A perspective on the use of ecological momentary assessment and intervention to promote stroke recovery and rehabilitation

Motivated by recent advances in technologies, ecological momentary assessment (EMA), and ecological momentary intervention (EMI) have seen a rise in behavioral medicine research that in real-time, informs the context for the behavior and prompts interventions to change that behavior in the natural setting when necessary. However, EMA and EMI have yet to be fully embraced in the field of stroke rehabilitation. Our objective is to provide a theoretically based perspective for the combined and synergistic use of EMA and EMI to promote person-centered, recovery-based durable changes in functional movement behaviors of stroke survivors. Research abounds for non-stroke populations with emerging evidence for the benefits of using real-time data capture techniques (i.e. EMA) coupled with EMI to better customize the content and timing of interventions to the inherent fluctuations in state and context that encompass the target behavior. We review existing EMA and EMI literature broadly in behavioral medicine and psychological science to identify how real-time repeated sampling technology has been used in the context of stroke rehabilitation and to delineate the pros and cons of this approach in general with non-stroke populations. We propose a coupled EMA and EMI strategy be used in conjunction with existing stroke recovery and rehabilitation practices. There is tremendous potential to effectively personalize recovery-promoting interventions to achieve durable behavior change, and importantly, shift the focus of rehabilitation practice from the health-care provider and clinical environment to the individual and their lived experience in the home and community.

Relationships between accelerometry and general compensatory movements of the upper limb after stroke

Background

Standardized assessments are used in rehabilitation clinics after stroke to measure restoration versus compensatory movements of the upper limb. Accelerometry is an emerging tool that can bridge the gap between in- and out-of-clinic assessments of the upper limb, but is limited in that it currently does not capture the quality of a person’s movement, an important concept to assess compensation versus restoration. The purpose of this analysis was to characterize how accelerometer variables may reflect upper limb compensatory movement patterns after stroke.

Methods

This study was a secondary analysis of an existing data set from a Phase II, single-blind, randomized, parallel dose–response trial (NCT0114369). Sources of data utilized were: (1) a compensatory movement score derived from video analysis of the Action Research Arm Test (ARAT), and (2) calculated accelerometer variables quantifying time, magnitude and variability of upper limb movement from the same time point during study participation for both in-clinic and out-of-clinic recording periods.

Results

Participants had chronic upper limb paresis of mild to moderate severity. Compensatory movement scores varied across the sample, with a mean of 73.7 ± 33.6 and range from 11.5 to 188. Moderate correlations were observed between the compensatory movement score and each accelerometer variable. Accelerometer variables measured out-of-clinic had stronger relationships with compensatory movements, compared with accelerometer variables in-clinic. Variables quantifying time, magnitude, and variability of upper limb movement out-of-clinic had relationships to the compensatory movement score.

Conclusions

Accelerometry is a tool that, while measuring movement quantity, can also reflect the use of general compensatory movement patterns of the upper limb in persons with chronic stroke. Individuals who move their limbs more in daily life with respect to time and variability tend to move with less movement compensations and more typical movement patterns. Likewise, individuals who move their paretic limbs less and their non-paretic limb more in daily life tend to move with more movement compensations at all joints in the paretic limb and less typical movement patterns.

Implementation of Wearable Sensing Technology for Movement: Pushing Forward into the Routine Physical Rehabilitation Care Field

While the promise of wearable sensor technology to transform physical rehabilitation has been around for a number of years, the reality is that wearable sensor technology for the measurement of human movement has remained largely confined to rehabilitation research labs with limited ventures into clinical practice. The purposes of this paper are to: (1) discuss the major barriers in clinical practice and available wearable sensing technology; (2) propose benchmarks for wearable device systems that would make it feasible to implement them in clinical practice across the world and (3) evaluate a current wearable device system against the benchmarks as an example. If we can overcome the barriers and achieve the benchmarks collectively, the field of rehabilitation will move forward towards better movement interventions that produce improved function not just in the clinic or lab, but out in peoples' homes and communities.

Characterizing upper extremity motor behavior in the first week after stroke

Background

Animal models of brain recovery identify the first days after lesioning as a time of great flux in sensorimotor function and physiology. After rodent motor system lesioning, daily skill training in the less affected forelimb reduces skill acquisition in the more affected forelimb. We asked whether spontaneous human motor behaviors of the less affected upper extremity (UE) early after stroke resemble the animal training model, with the potential to suppress clinical recovery.

Methods

This prospective observational study used a convenience sample of patients (n = 25, mean 4.5 ±1.8) days after stroke with a wide severity range; Controls were hospitalized for non-neurological conditions (n = 12). Outcome measures were Accelerometry, Upper-Extremity Fugl-Meyer (UEFM), Action Research Arm Test (ARAT), Shoulder Abduction/ Finger Extension Test (SAFE), NIH Stroke Scale (NIHSS).

Results

Accelerometry indicated total paretic UE movement was reduced compared to controls, primarily due to a 44% reduction of bilateral UE use. Unilateral paretic movement was unchanged. Thus, movement shifted early after stroke; bilateral use was reduced and unilateral use of the non-paretic UE was increased by 77%. Low correlations between movement time and motor performance prompted an exploratory factor analysis (EFA) revealing a 2-component solution; motor performance tests load on one component (motor performance) whereas accelerometry-derived variables load on a second orthogonal component (quantity of movement).

Conclusions

Early after stroke, spontaneous overall UE movement is reduced, and movement shifts to unilateral use of the non-paretic UE. Two mechanisms that could influence motor recovery may already be in place 4.5 ± 1.8 days post stroke: (1) the overuse of the less affected UE, which could set the stage for learned non-use and (2) skill acquisition in the non-paretic limb that could impede recovery. Accurate UE motor assessment requires two independent constructs: motor performance and quantity of movement. These findings provide opportunities and measurement methods for studies to develop new behaviorally-based stroke recovery treatments that begin early after onset.

Quantifying Real-World Upper-Limb Activity Via Patient-Initiated Movement After Nerve Reconstruction for Upper Brachial Plexus Injury

BACKGROUND

A critical concept in brachial plexus reconstruction is the accurate assessment of functional outcomes. The current standard for motor outcome assessment is clinician-elicited, outpatient clinic-based, serial evaluation of range of motion and muscle power. However, discrepancies exist between such clinical measurements and actual patient-initiated use. We employed emerging technology in the form of accelerometry-based motion detectors to quantify real-world arm use after brachial plexus surgery.

OBJECTIVE

To evaluate (1) the ability of accelerometry-based motion detectors to assess functional outcome and (2) the real-world arm use of patients after nerve transfer for brachial plexus injury, through a pilot study.

METHODS

Five male patients who underwent nerve transfer after brachial plexus injury wore bilateral motion detectors for 7 d. The patients also underwent range-of-motion evaluation and completed multiple patient-reported outcome surveys.

RESULTS

The average age of the recruits was 41 yr (±17 yr), and the average time from operation was 2 yr (±1 yr). The VT (time of use ratio) for the affected side compared to the unaffected side was 0.73 (±0.27), and the VM (magnitude ratio) was 0.63 (±0.59). VT strongly and positively correlated with shoulder flexion and shoulder abduction: 0.97 (P = .008) and 0.99 (P = .002), respectively.

CONCLUSION

Accelerometry-based activity monitors can successfully assess real-world functional outcomes after brachial plexus reconstruction. This pilot study demonstrates that patients after nerve transfer are utilizing their affected limbs significantly in daily activities and that recovery of shoulder function is critical.

Quantifying dosage of physical therapy using lower body kinematics: a longitudinal pilot study on early post-stroke individuals

Background

While therapy is an important part of the recovery process, there is a lack of quantitative data detailing the “dosage” of therapy received due to the limitations on in/outpatient accessibility and mobility. Advances in wearable sensor technology have allowed us to obtain an unprecedented glimpse into joint-level kinematics in an unobtrusive manner. The objective of this observational longitudinal pilot study was to evaluate the relations between lower body joint kinematics during therapy and functional gait recovery over the first three months after stroke.

Methods

Six individuals with subacute stroke (< 1 month) were monitored for a total of 59 one-hour physical therapy sessions including gait and non-gait activities. Participants donned a heart rate monitor and an inertial motion capture system to measure full lower body joint kinematics during each therapy session. Linear mixed regression models were used to examine relations between functional gait recovery (speed) and activity features including total joint displacements, defined as amount of motion (AoM), step number, change in heart rate (∆HR), and types of tasks performed.

Results

All activity features including AoM, step number, types of tasks performed (all p < 0.01), and ∆HR (p < 0.05) showed strong associations with gait speed. However, AoM (R² = 32.1%) revealed the greatest explained variance followed by step number (R² = 14.1%), types of tasks performed (R² = 8.0%) and ∆HR (R² = 5.8%). These relations included both gait and non-gait tasks. Contrary to our expectations, we did not observe a greater relation of functional recovery to motion in the impaired limb (R² = 27.8%) compared to the unimpaired limb (R² = 32.9%).

Conclusions

This proof-of-concept study shows that recording joint kinematics during gait therapy longitudinally after stroke is feasible and yields important information for the recovery process. These initial results suggest that compared to step number, more holistic outcome measures such as joint motions may be more informative and help elucidate the dosage of therapy.

Towards the Design of a Ring Sensor-based mHealth System to Achieve Optimal Motor Function in Stroke Survivors

Maximizing the motor practice in stroke survivors' living environments may significantly improve the functional recovery of their stroke-affected upper-limb. A wearable system that can continuously monitor upper-limb performance has been considered as an effective clinical solution for its potential to provide patient-centered, data-driven feedback to improve the motor dosage. Towards that end, we investigate a system leveraging a pair of finger-worn, ring-type accelerometers capable of monitoring both gross-arm and fine-hand movements that are clinically relevant to the performance of daily activities. In this work, we conduct a mixed-methods study to (1) quantitatively evaluate the efficacy of finger-worn accelerometers in measuring clinically relevant information regarding stroke survivors' upper-limb performance, and (2) qualitatively investigate design requirements for the self-monitoring system, based on data collected from 25 stroke survivors and seven occupational therapists. Our quantitative findings demonstrate strong face and convergent validity of the finger-worn accelerometers, and its responsiveness to changes in motor behavior. Our qualitative findings provide a detailed account of the current rehabilitation process while highlighting several challenges that therapists and stroke survivors face. This study offers promising directions for the design of a self-monitoring system that can encourage the affected limb use during stroke survivors' daily living.

Actigraphic measurement of the upper limbs movements in acute stroke patients

Background

Stroke units provide patients with a multiparametric monitoring of vital functions, while no instruments are actually available for a continuous monitoring of patients motor performance. Our aim was to develop an actigraphic index able both to identify the paretic limb and continuously monitor the motor performance of stroke patients in the stroke unit environment.

Methods

Twenty consecutive acute stroke patients (mean age 69.2 years SD 10.1, 8 males and 12 females) and 17 bed-restrained patients (mean age 70.5 years SD 7.3, 7 males and 10 females) hospitalized for orthopedic diseases of the lower limbs, but not experiencing neurological symptoms, were enrolled. This last group represented our control group. The motor activity of arms was recorded for 24 h using two programmable actigraphic systems showing off as wrist-worn watches. The firmware segmented the acquisition in epochs of 1 minute and for each epoch calculates two motor activity indices: MA_e1 (Epoch-related Motor Activity index) and MA_e2 (Epoch-related Motor Activity index 2). MA_e1 is defined as the standard deviation of the acceleration module and MA_e2 as the module of the standard deviation of acceleration components. To describe the 24 h motor performance of each limb, we calculated the mean value of MA_e1 and MA_e2 (respectively MA_{1_24h} and MA_{2_24h}). Then we obtained two Asymmetry Rate Indices: AR_{1_24h} and AR_{2_24h} to show the motor activity prevalence. AR_{1_24h} refers to the asymmetry index between the values of MA_e1 of both arms and AR_{2_24h} to MA_e2 values.

The stroke patients were clinically evaluated by NIHSS at the beginning (NIHSS_T0) and at the end (NIHSS_T1) of the 24 h actigraphic recordings.

Results

Both MA_{1_24h} and MA_{2_24h} indices were smaller in the paretic than in the unaffected arm (respectively p = 0.004 and p = 0.004). AR_{2_24h} showed a better capability (95% of paretic arms correctly identified, Phi Coefficient: 0.903) to discriminate the laterality of the clinical deficit than AR_{1_24h} (85% of paretic arms correctly identified, Phi Coefficient: 0,698). We also found that AR_{1_24h} did not differ between the two groups of patients while AR_{2_24h} was greater in stroke patients than in controls and positively correlated with NIHSS total scores (r: 0.714, p < 0.001 for NIHSS, IC95%: 0.42–0.90) and with the sub-score relative to the paretic upper limb (r: 0.812, p < 0.001, IC95%: 0.62–0.96).

Conclusions

Our data show that actigraphic monitoring of upper limbs can detect the laterality of the motor deficit and measure the clinical severity. These findings suggest that the above described actigraphic system could implement the existing multiparametric monitoring in stroke units.

sEMG-Based Trunk Compensation Detection in Rehabilitation Training

Stroke patients often use trunk to compensate for impaired upper limb motor function during upper limb rehabilitation training, which results in a reduced rehabilitation training effect. Detecting trunk compensations can improve the effect of rehabilitation training. This study investigates the feasibility of a surface electromyography-based trunk compensation detection (sEMG-bTCD) method. Five healthy subjects and nine stroke subjects with cognitive and comprehension skills were recruited to participate in the experiments. The sEMG signals from nine superficial trunk muscles were collected during three rehabilitation training tasks (reach-forward-back, reach-side-to-side, and reach-up-to-down motions) without compensation and with three common trunk compensations [lean-forward (LF), trunk rotation (TR), and shoulder elevation (SE)]. Preprocessing like filtering, active segment detection was performed and five time domain features (root mean square, variance, mean absolute value (MAV), waveform length, and the fourth order autoregressive model coefficient) were extracted from the collected sEMG signals. Excellent TCD performance was achieved in healthy participants by using support vector machine (SVM) classifier (LF: accuracy = 94.0%, AUC = 0.97, F1 = 0.94; TR: accuracy = 95.8%, AUC = 0.99, F1 = 0.96; SE: accuracy = 100.0%, AUC = 1.00, F1 = 1.00). By using SVM classifier, TCD performance in stroke participants was also obtained (LF: accuracy = 74.8%, AUC = 0.90, F1 = 0.73; TR: accuracy = 67.1%, AUC = 0.85, F1 = 0.71; SE: accuracy = 91.3%, AUC = 0.98, F1 = 0.90). Compared with the methods based on cameras or inertial sensors, better detection performance was obtained in both healthy and stroke participants. The results demonstrated the feasibility of the sEMG-bTCD method, and it helps to prompt the stroke patients to correct their incorrect posture, thereby improving the effectiveness of rehabilitation training.

Upper Limb Performance in Daily Life Improves Over the First 12 Weeks Poststroke

Background. Upper limb (UL) performance, or use, in daily life is complex and likely influenced by many factors. While the recovery trajectory of UL impairment poststroke is well documented, little is known about the recovery trajectory of sensor-measured UL performance in daily life early after stroke and the potential moderating role of psychosocial factors. Objective. To examine the recovery trajectory of UL performance within the first 12 weeks poststroke and characterize the potential moderating role of belief, confidence, and motivation on UL performance. Methods. This was a longitudinal, prospective cohort study quantifying UL performance and related psychosocial factors early after stroke. UL performance was quantified via bilateral, wrist-worn accelerometers over 5 assessment sessions for 24 hours. Belief, confidence, and motivation to use the paretic UL, and self-perceived barriers to UL recovery were quantified via survey. Change in 4 accelerometer variables and the moderating role of psychosocial factors was tested using hierarchical linear modeling. The relationship between self-perceived barriers and UL performance was tested via Spearman rank-order correlation analysis. Results. UL performance improved over the first 12 weeks after stroke. Belief, confidence, and motivation did not moderate UL performance over time. There was a negative relationship between UL performance and self-perceived barriers to UL recovery at week 2, which declined over time. Conclusions. Sensor-measured UL performance can improve early after stroke. Early after stroke, rehabilitation interventions may not need to directly target belief, confidence, and motivation but may instead focus on reducing self-perceived barriers to UL recovery.

Measuring Reliability of Movement With Accelerometry: Fitbit® Versus ActiGraph®

OBJECTIVE

We sought to determine the reliability of the Fitbit^® Flex™ compared with the ActiGraph^® Bluetooth^® Smart wGT3X-BT wireless activity monitor and to contribute to the clinical utility of accelerometry measurement of upper extremity (UE) movement.

METHOD

Two studies were conducted at different sites with healthy adult participants. In Study 1, participants wore both accelerometers on both wrists during everyday activities for a 24-hr period. In Study 2, participants wore both accelerometers on the dominant wrist for 4 hr during an active period of the day. All participants wore the accelerometers during regular daily activities.

RESULTS

Data recorded from the Fitbit and the ActiGraph showed a high positive correlation; however, the Fitbit recorded significantly fewer movements than the ActiGraph.

CONCLUSION

Although the Fitbit and the ActiGraph measure UE activity similarly, the Fitbit was not as sensitive as the ActiGraph. This study provides informative data on the clinical utility of the Fitbit compared with the ActiGraph.

A novel upper-limb function measure derived from finger-worn sensor data collected in a free-living setting

The use of wrist-worn accelerometers has recently gained tremendous interest among researchers and clinicians as an objective tool to quantify real-world use of the upper limbs during the performance of activities of daily living (ADLs). However, wrist-worn accelerometers have shown a number of limitations that hinder their adoption in the clinic. Among others, the inability of wrist-worn accelerometers to capture hand and finger movements is particularly relevant to monitoring the performance of ADLs. This study investigates the use of finger-worn accelerometers to capture both gross arm and fine hand movements for the assessment of real-world upper-limb use. A system of finger-worn accelerometers was utilized to monitor eighteen neurologically intact young adults while performing nine motor tasks in a laboratory setting. The system was also used to monitor eighteen subjects during the day time of a day in a free-living setting. A novel measure of real-world upper-limb function—comparing the duration of activities of the two limbs—was derived to identify which upper limb subjects predominantly used to perform ADLs. Two validated handedness self-reports, namely the Waterloo Handedness Questionnaire and the Fazio Laterality Inventory, were collected to assess convergent validity. The analysis of the data recorded in the laboratory showed that the proposed measure of upper-limb function is suitable to accurately detect unilateral vs. bilateral use of the upper limbs, including both gross arm movements and fine hand movements. When applied to recordings collected in a free-living setting, the proposed measure showed high correlation with self-reported handedness indices (i.e., ρ = 0.78 with the Waterloo Handedness Questionnaire scores and ρ = 0.77 with the Fazio Laterality Inventory scores). The results herein presented establish face and convergent validity of the proposed measure of real-world upper-limb function derived using data collected by means of finger-worn accelerometers.

Sensor Measures of Symmetry Quantify Upper Limb Movement in the Natural Environment Across the Lifespan

Knowledge of upper limb activity in the natural environment is critical for evaluating the effectiveness of rehabilitation services. Wearable sensors allow efficient collection of these data and have the potential to be less burdensome than self-report measures of activity. Sensors can capture many different variables of activity and daily performance, many of which could be useful in identifying deviation from typical movement behavior or measuring outcomes from rehabilitation interventions. Although it has potential, sensor measurement is just emerging, and there is a lack of consensus regarding which variables of daily performance are valid, sensitive, specific, and useful. We propose that symmetry of full-day upper limb movement is a key variable. We describe here that symmetry is valid, robustly observed within a narrow range across the lifespan in typical development, and shows evidence of being different in populations with neuromotor impairment. Key next steps include the determination of sensitivity, specificity, minimal detectable change, and minimal clinically important change/difference. This information is needed to determine whether an individual belongs to the typical or atypical group, whether change has occurred, and whether that change is beneficial.

Consideration of Dose and Timing When Applying Interventions After Stroke and Spinal Cord Injury

BACKGROUND AND PURPOSE

Nearly 4 decades of investigation into the plasticity of the nervous system suggest that both timing and dose could matter. This article provides a synopsis of our lectures at the IV STEP meeting, which presented a perspective of current data on the issues of timing and dose for adult stroke and spinal cord injury motor rehabilitation.

SUMMARY OF KEY POINTS

For stroke, the prevailing evidence suggests that greater amounts of therapy do not result in better outcomes for upper extremity interventions, regardless of timing. Whether or not greater amounts of therapy result in better outcomes for lower extremity and mobility interventions needs to be explicitly tested. For spinal cord injury, there is a complex interaction of timing postinjury, task-specificity, and the microenvironment of the spinal cord. Inflammation appears to be a key determinant of whether or not an intervention will be beneficial or maladaptive, and specific retraining of eccentric control during gait may be necessary.

RECOMMENDATIONS FOR CLINICAL PRACTICE

To move beyond the limitations of our current interventions and to effectively reach nonresponders, greater precision in task-specific interventions that are well-timed to the cellular environment may hold the key. Neurorehabilitation that ameliorates persistent deficits, attains greater recovery, and reclaims nonresponders will decrease institutionalization, improve quality of life, and prevent multiple secondary complications common after stroke and spinal cord injury.

Enabling Stroke Rehabilitation in Home and Community Settings: A Wearable Sensor-Based Approach for Upper-Limb Motor Training

High-dosage motor practice can significantly contribute to achieving functional recovery after a stroke. Performing rehabilitation exercises at home and using, or attempting to use, the stroke-affected upper limb during Activities of Daily Living (ADL) are effective ways to achieve high-dosage motor practice in stroke survivors. This paper presents a novel technological approach that enables 1) detecting goal-directed upper limb movements during the performance of ADL, so that timely feedback can be provided to encourage the use of the affected limb, and 2) assessing the quality of motor performance during in-home rehabilitation exercises so that appropriate feedback can be generated to promote high-quality exercise. The results herein presented show that it is possible to detect 1) goal-directed movements during the performance of ADL with a \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$c$ \end{document}-statistic of 87.0% and 2) poorly performed movements in selected rehabilitation exercises with an \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$F$ \end{document}-score of 84.3%, thus enabling the generation of appropriate feedback. In a survey to gather preliminary data concerning the clinical adequacy of the proposed approach, 91.7% of occupational therapists demonstrated willingness to use it in their practice, and 88.2% of stroke survivors indicated that they would use it if recommended by their therapist.

Contralateral effects of unilateral training: sparing of muscle strength and size after immobilization

The contralateral effects of unilateral strength training, known as cross-education of strength, date back well over a century. In the last decade, a limited number of studies have emerged demonstrating the preservation or "sparing" effects of cross-education during immobilization. Recently published evidence reveals that the sparing effects of cross-education show muscle site specificity and involve preservation of muscle cross-sectional area. The new research also demonstrates utility of training with eccentric contractions as a potent stimulus to preserve immobilized limb strength across multiple modes of contraction. The cumulative data in nonclinical settings suggest that cross-education can completely abolish expected declines in strength and muscle size in the range of ∼13% and ∼4%, respectively, after 3-4 weeks of immobilization of a healthy arm. The evidence hints towards the possibility that unique mechanisms may be involved in preservation effects of cross-education, as compared with those that lead to functional improvements under normal conditions. Cross-education effects after strength training appear to be larger in clinical settings, but there is still only 1 randomized clinical trial demonstrating the potential utility of cross-education in addition to standard treatment. More work is necessary in both controlled and clinical settings to understand the potential interaction of neural and muscle adaptations involved in the observed sparing effects, but there is growing evidence to advocate for the clinical utility of cross-education.

Identifying compensatory movement patterns in the upper extremity using a wearable sensor system

OBJECTIVE

Movement impairments such as those due to stroke often result in the nervous system adopting atypical movements to compensate for movement deficits. Monitoring these compensatory patterns is critical for improving functional outcomes during rehabilitation. The purpose of this study was to test the feasibility and validity of a wearable sensor system for detecting compensatory trunk kinematics during activities of daily living.

APPROACH

Participants with no history of neurological impairments performed reaching and manipulation tasks with their upper extremity, and their movements were recorded by a wearable sensor system and validated using a motion capture system. Compensatory movements of the trunk were induced using a brace that limited range of motion at the elbow.

MAIN RESULTS

Our results showed that the elbow brace elicited compensatory movements of the trunk during reaching tasks but not manipulation tasks, and that a wearable sensor system with two sensors could reliably classify compensatory movements (~90% accuracy).

SIGNIFICANCE

These results show the potential of the wearable system to assess and monitor compensatory movements outside of a lab setting.

A Method for Quantifying Upper Limb Performance in Daily Life Using Accelerometers

A key reason for referral to rehabilitation services after stroke and other neurological conditions is to improve one's ability to function in daily life. It has become important to measure a person's activities in daily life, and not just measure their capacity for activity in the structured environment of a clinic or laboratory. A wearable sensor that is now enabling measurement of daily movement is the accelerometer. Accelerometers are commercially-available devices resembling large wrist watches that can be worn throughout the day. Data from accelerometers can quantify how the limbs are engaged to perform activities in peoples' homes and communities. This report describes a methodology to collect accelerometry data and turn it into clinically-relevant information. First, data are collected by having the participant wear two accelerometers (one on each wrist) for 24 h or longer. The accelerometry data are then downloaded and processed to produce four different variables that describe key aspects of upper limb activity in daily life: hours of use, use ratio, magnitude ratio, and the bilateral magnitude. Density plots can be constructed that visually represent the data from the 24 h wearing period. The variables and their resultant density plots are highly consistent in neurologically-intact, community-dwelling adults. This striking consistency makes them a useful tool for determining if upper limb daily performance is different from normal. This methodology is appropriate for research studies investigating upper limb dysfunction and interventions designed to improve upper limb performance in daily life in people with stroke and other patient populations. Because of its relative simplicity, it may not be long before it is also incorporated in clinical neurorehabilitation practice.

Does Task-Specific Training Improve Upper Limb Performance in Daily Life Poststroke?

BACKGROUND

A common assumption is that changes in upper limb (UL) capacity, or what an individual is capable of doing, translates to improved UL performance in daily life, or what an individual actually does. This assumption should be explicitly tested for individuals with UL paresis poststroke.

OBJECTIVE

To examine changes in UL performance after an intensive, individualized, progressive, task-specific UL intervention for individuals at least 6 months poststroke.

METHODS

Secondary analysis on 78 individuals with UL paresis who participated in a phase II, single-blind, randomized parallel dose-response trial. Participants were enrolled in a task-specific intervention for 8 weeks. Participants were randomized into 1 of 4 treatment groups with each group completing different amounts of UL movement practice. UL performance was assessed with bilateral, wrist-worn accelerometers once a week for 24 hours throughout the duration of the study. The 6 accelerometer variables were tested for change and the influence of potential modifiers using hierarchical linear modeling.

RESULTS

No changes in UL performance were found on any of the 6 accelerometer variables used to quantify UL performance. Neither changes in UL capacity nor the overall amount of movement practice influenced changes in UL performance. Stroke chronicity, baseline UL capacity, concordance, and ADL status significantly increased the baseline starting points but did not influence the rate of change (slopes) for participants.

CONCLUSIONS

Improved motor capacity resulting from an intensive outpatient UL intervention does not appear to translate to increased UL performance outside the clinic.

Upper Limb Rehabilitation in People With Multiple Sclerosis

Background. There has been an increasing research interest in upper limb rehabilitation in multiple sclerosis (MS). The current changes in the research field inquire a new literature review. Objective. This systematic review aimed to provide an overview of the upper limb rehabilitation strategies in people with MS (PwMS). Methods. Articles published in PubMed and Web of Knowledge were selected when written in English, published in the past 25 years, peer reviewed, that included at least 5 PwMS, and described the effects of an intervention study including rehabilitation strategies targeting the upper limbs. Included articles were screened based on title/abstract and full text by 2 independent reviewers. Results. Thirty articles met the criteria and were included for data extraction. Only half of the included studies investigated the effects of a training program specially targeted toward the upper limbs, while in the other studies, a general whole body therapy was used. The therapy content and dosage varied greatly between the different included studies. Multidisciplinary and robot-based rehabilitation were the most investigated rehabilitation strategies and showed to improve upper limb capacity. Strength and endurance training improved the upper limb body functions and structures but did not influence the upper limb capacity and performance. Conclusions. The results of this systematic review indicated that different types of upper limb rehabilitation strategies can improve upper limb function in PwMS. Further research is necessary to compare directly the effects of different rehabilitation strategies and to investigate the optimal therapy dosage according to the upper limb disability level.

Changes in Upper-Extremity Functional Capacity and Daily Performance During Outpatient Occupational Therapy for People With Stroke

OBJECTIVE

This study explored how upper-extremity (UE) functional capacity and daily performance change during the course of outpatient rehabilitation in people with stroke.

METHOD

Fifteen participants receiving outpatient occupational therapy services for UE paresis poststroke were enrolled. UE motor capacity was measured with the Action Research Arm Test (ARAT), and UE performance was measured using bilateral, wrist-worn accelerometers. Measurements were taken at or near the start of therapy, at every 10th visit or every 30 days throughout the duration of services, and at discharge.

RESULTS

Three patterns were observed: (1) increase in ARAT scores and more normalized accelerometry profiles, (2) increase in ARAT scores but no change in accelerometry profiles, and (3) no change in ARAT scores or in accelerometry profiles.

CONCLUSION

UE performance in daily life was highly variable, with inconsistencies between change in UE capacity and change in UE performance. UE capacity and performance are important constructs to assess separately during rehabilitation.

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

The ultimate goal of upper-limb rehabilitation after stroke is to promote real-world use, that is, use of the paretic upper-limb in everyday activities outside the clinic or laboratory. Although real-world use can be collected through self-report questionnaires, an objective indicator is preferred. Accelerometers are a promising tool. The current paper aims to explore the feasibility of accelerometers to measure upper-limb use after stroke and discuss the translation of this measurement tool into clinical practice. Accelerometers are non-invasive, wearable sensors that measure movement in arbitrary units called activity counts. Research to date indicates that activity counts are a reliable and valid index of upper-limb use. While most accelerometers are unable to distinguish between the type and quality of movements performed, recent advancements have used accelerometry data to produce clinically meaningful information for clinicians, patients, family and care givers. Despite this, widespread uptake in research and clinical environments remains limited. If uptake was enhanced, we could build a deeper understanding of how people with stroke use their arm in real-world environments. In order to facilitate greater uptake, however, there is a need for greater consistency in protocol development, accelerometer application and data interpretation.

Validation of a Clinical Test of Thoracolumbar Dissociation in Chronic Low Back Pain

STUDY DESIGN

Clinical test validation.

OBJECTIVES

Preliminary study of concurrent and discriminant validity of a clinical test of thoracolumbar dissociation.

BACKGROUND

Control deficits of back muscles and trunk movement are common in chronic/recurrent low back pain (LBP). A reliable clinical test to rate an individual's ability to dissociate lumbopelvic movement from the thoracolumbar region has been described. This test rates the performance quality of 5 key aspects against criterion standards.

METHODS

Concurrent validity was examined by comparison of clinical test scores (overall score and each individual criterion) against spine kinematics. Discriminant validity was evaluated by comparison of scores between pain-free controls and participants with LBP. A receiver operating characteristic curve was calculated to determine the optimal cutoff or score to differentiate between good and poor performers.

RESULTS

Concurrent validity was supported by the significant correlation between the total score and motion of the T5 vertebra relative to the S1 vertebra (P<.05). Scores for some (4 correlations of 14 measures) but not all individual criteria were correlated with the kinematic features that each criterion was expected to reflect. Discriminant validity was supported by higher test scores for pain-free controls than for participants with LBP after 2 minutes of training (P = .045). Scores of less than 5.5 were more prevalent in the LBP group (pretraining LBP versus control, 72% versus 35%; P = .008; posttraining LBP versus control, 48% versus 16%; P = .018).

CONCLUSION

This preliminary study of concurrent and discriminant validity of the test provides a foundation to further investigate its utility to characterize thoracolumbar movement patterns in individuals with LBP.

A Framework to Automate Assessment of Upper-Limb Motor Function Impairment: A Feasibility Study

Standard upper-limb motor function impairment assessments, such as the Fugl-Meyer Assessment (FMA), are a critical aspect of rehabilitation after neurological disorders. These assessments typically take a long time (about 30 min for the FMA) for a clinician to perform on a patient, which is a severe burden in a clinical environment. In this paper, we propose a framework for automating upper-limb motor assessments that uses low-cost sensors to collect movement data. The sensor data is then processed through a machine learning algorithm to determine a score for a patient’s upper-limb functionality. To demonstrate the feasibility of the proposed approach, we implemented a system based on the proposed framework that can automate most of the FMA. Our experiment shows that the system provides similar FMA scores to clinician scores, and reduces the time spent evaluating each patient by 82%. Moreover, the proposed framework can be used to implement customized tests or tests specified in other existing standard assessment methods.