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.

Using Wearable Sensors and Machine Learning Models to Separate Functional Upper Extremity Use From Walking-Associated Arm Movements

OBJECTIVE

To improve measurement of upper extremity (UE) use in the community by evaluating the feasibility of using body-worn sensor data and machine learning models to distinguish productive prehensile and bimanual UE activity use from extraneous movements associated with walking.

DESIGN

Comparison of machine learning classification models with criterion standard of manually scored videos of performance in UE prosthesis users.

SETTING

Rehabilitation hospital training apartment.

PARTICIPANTS

Convenience sample of UE prosthesis users (n=5) and controls (n=13) similar in age and hand dominance (N=18).

INTERVENTIONS

Participants were filmed executing a series of functional activities; a trained observer annotated each frame to indicate either UE movement directed at functional activity or walking. Synchronized data from an inertial sensor attached to the dominant wrist were similarly classified as indicating either a functional use or walking. These data were used to train 3 classification models to predict the functional versus walking state given the associated sensor information. Models were trained over 4 trials: on UE amputees and controls and both within subject and across subject. Model performance was also examined with and without preprocessing (centering) in the across-subject trials.

MAIN OUTCOME MEASURE

Percent correct classification.

RESULTS

With the exception of the amputee/across-subject trial, at least 1 model classified >95% of test data correctly for all trial types. The top performer in the amputee/across-subject trial classified 85% of test examples correctly.

CONCLUSIONS

We have demonstrated that computationally lightweight classification models can use inertial data collected from wrist-worn sensors to reliably distinguish prosthetic UE movements during functional use from walking-associated movement. This approach has promise in objectively measuring real-world UE use of prosthetic limbs and may be helpful in clinical trials and in measuring response to treatment of other UE pathologies.

Is a coded physical activity diary valid for assessing physical activity level and energy expenditure in stroke patients?

Objectives

to determine the concurrent validity of a physical activity diary for measuring physical activity level and total energy expenditure in hospitalized stroke patients.

Method

Sixteen stroke patients kept coded activity diaries and wore SenseWear Pro2 multi-sensor activity monitors during daytime hours for one day. A researcher observed the patients and completed a diary. Data from the patients' diaries were compared with observed and measured data to determine total activity (METs*minutes), activity level and total energy expenditure.

Results

Spearman correlations between the patients' and researchers' diaries revealed a high correlation for total METs*minutes (r_s = 0.75, p<0.01) for sedentary (r_s = 0.74,p<0.01) and moderate activities (r_s = 0.71,p<0.01) and a very high correlation (r_s = 0.92, p<0.01) for the total energy expenditure. Comparisons between the patients' diaries and activity monitor data revealed a low correlation (r_s 0.29) for total METs*minutes and energy expenditure.

Conclusion

Coded self-monitoring activity diaries appear feasible as a low-tech alternative to labor-intensive observational diaries for determining sedentary, moderate, and total physical activity and for quantifying energy expenditure in hospitalized stroke patients. Given the poor correlation with objective measurements of physical activity, however, further research is needed to validate its use against a gold-standard measure of physical activity intensity and energy expenditure.

Using an accelerometer for analyzing a reach-to-grasp movement after stroke

The purpose of this study was using an accelerometer to access the kinematics of reach-to-grasp movements in subjects with hemiparesis. Eight subjects (59.4 ± 6.9 years old) with chronic hemiparesis (50.9 ± 25.8 months post-stroke) participated in this study. Kinematic assessment was performed using a triaxial accelerometer (EMG Systems, Brazil) attached to the subjects' forearm. Ten reach-to-grasp movements of grabbing a 500ml-size bottle were performed by the subjects with the paretic and the non-paretic upper limbs (ULs). The following space-temporal variables were calculated and used to compare the paretic and non-paretic ULs: movement time (MT), time to reach the peak velocity, absolute and relative (TPV and TPV%MT), relative deceleration duration (DEC%MT), time to peak acceleration (TPA) and peak hand acceleration (PA). Movements were slower in the paretic UL with increased MT, TPA and DEC. The accelerometer allowed to identify of changes in reaching-to-grasp movements of subjects with hemiparesis. When complex systems are not available, accelerometers can be an alternative to measure UL movements.

Assessment of upper extremity impairment, function, and activity after stroke: foundations for clinical decision making

The purpose of this review is to provide a comprehensive approach for assessing the upper extremity (UE) after stroke. First, common UE impairments and how to assess them are briefly discussed. Although multiple UE impairments are typically present after stroke, the severity of one's impairment, paresis, is the primary determinant of UE functional loss. Second, UE function is operationally defined and a number of clinical measures are discussed. It is important to consider how impairment and loss of function affect UE activity outside of the clinical environment. Thus, this review also identifies accelerometry as an objective method for assessing UE activity in daily life. Finally, the role that each of these levels of assessment should play in clinical decision making is discussed to optimize the provision of stroke rehabilitation services.

Clinical reality of measuring upper-limb ability in neurologic conditions: a systematic review

OBJECTIVE

To review the psychometric properties and clinical utility of upper-limb measurement tools in people with neurologic conditions to provide recommendations for practice.

DATA SOURCES

MEDLINE, CINAHL, EMBASE, PEDro, and AMED.

STUDY SELECTION

Independent reviewers searched, selected, and extracted data from articles that assessed reliability, validity, ability to detect change, and clinical utility of measures of the upper limb in adult neurologic conditions.

DATA EXTRACTION

Measures with good psychometrics and 8 or higher (out of 10) clinical utility scores were recommended.

DATA SYNTHESIS

The searches identified 31 measures of the upper limb. However, only 2 measures fulfilled all of the psychometric and clinical utility criteria; the Box and Block Test and the Action Research Arm Test.

CONCLUSIONS

The Box and Block and the Action Research Arm Tests produce robust data and are feasible for use in clinical practice. Future development of new or existing measures should ensure the construct and content validity of the measure is clearly identified, standardized guidelines are easily available, and ensure that it is individualized and contemporary. Attention to measures of upper-limb activity for people who are unable to grip objects is also needed.

Review of physical activity measurement using accelerometers in older adults: considerations for research design and conduct

OBJECTIVE

Accelerometers are being increasingly used in studies of physical activity (PA) among older adults, however the use of these monitors requires some specialized knowledge and up-to-date information on technological innovations. The purpose of this review article is to provide researchers with a guide to some commonly-used accelerometers in order to better design and conduct PA research with older adults.

METHODS

A literature search was conducted to obtain all available literature on commonly-used accelerometers in older adult samples with specific attention to articles discussing research design.

RESULTS

The use of accelerometers in older adults requires a basic understanding of the type being used, rationale for their placement, and attention to calibration when needed. The updated technology in some monitors should make study conduct less difficult, however comparison studies of the newer versus the older generation models will be needed.

CONCLUSIONS

Careful considerations for design and conduct of accelerometer research as outlined in this review should help to enhance the quality and comparability of future research studies.