Validity of Novel Outcome Measures for Hand Function Performance After Stroke Using Egocentric Video

 This is just assessments and doesn't get survivors recovered, so was a waste of time.

Validity of Novel Outcome Measures for Hand Function Performance After Stroke Using Egocentric Video

Meng-Fen Tsai, MEng https://orcid.org/0000-0002-4594-7463, Rosalie H. Wang, PhD, and José Zariffa, PhD jose.zariffa@utoronto.caView all authors and affiliations

Volume 37, Issue 2-3

https://doi.org/10.1177/15459683231159663

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Abstract

Background

Evaluating upper limb (UL) interventions after stroke calls for outcome measures that describe impact on daily life in the community. UL use ratio has been used to quantify the performance domain of UL function, but generally focuses on arm use only. A hand use ratio could provide additional information about UL function after stroke. Additionally, a ratio based on the role of the more-affected hand in bilateral activities (stabilizer or manipulator) may also reflect hand function recovery. Egocentric video is a novel modality that can record both dynamic and static hand use and hand roles at home after stroke.

Objective

To validate hand use and hand role ratios from egocentric video against standardized clinical UL assessments.

Methods

Twenty-four stroke survivors recorded daily tasks in a home simulation laboratory and their daily routines at home using egocentric cameras. Spearman’s correlation was used to compare the ratios with the Fugl-Meyer Assessment-Upper Extremity (FMA-UE), Action Research Arm Test (ARAT), and Motor Activity Log-30 (MAL, Amount of Use (AoU), and Quality of Movement (QoM)).

Results

Hand use ratio significantly correlated with the FMA-UE (0.60, 95% CI: 0.26, 0.81), ARAT (0.44, CI: 0.04, 0.72), MAL-AoU (0.80, CI: 0.59, 0.91), and MAL-QoM (0.79, CI: 0.57, 0.91). Hand role ratio had no significant correlations with the assessments.

Conclusion

Hand use ratio automatically extracted from egocentric video, but not hand role ratio, was found to be a valid measure of hand function performance in our sample. Further investigation is necessary to interpret hand role information.

Introduction

Upper limb (UL) function is one of the determinants of independence in activities of daily living (ADLs) after stroke. To evaluate the ultimate impact of novel treatments for UL function in daily life, an outcome measure that captures UL function outside of clinical settings is required. The International Classification of Functioning, Disability and Health (ICF) describes the activity domain of function as containing the sub-domains of performance and capacity; the former measures the function demonstrated in an individual’s living environment and the latter measures their highest function in a standardized environment.¹ Measuring UL function in the community belongs to the performance domain and corresponds to only 2 standardized clinical assessments: Motor Activity Log (MAL)² and Stroke Impact Scale.³ However, both assessments are self-reported questionnaires and may be limited by response bias and cognitive issues. Objective assessments of UL performance are required to evaluate UL function for community-dwelling stroke survivors.

To address this need, UL use ratio has been proposed as a sensor-based measurement that quantifies UL performance and has been applied in various environments. The concept is based on describing the amount of more-affected limb use as a fraction of the amount of less-affect limb use. The UL use ratio is very stable and close to one among healthy individuals,⁴ however, the ratios reported for stroke survivors vary between studies.^5,6 Most studies that reported UL use ratios used wrist-worn devices, such that the ratios described the arm use of stroke survivors rather than hand use.^7-9 In contrast, in clinical UL assessments, arm function, and hand function are measured in different subtests to separately evaluate reaching and grasping, such as in the Fugl-Meyer Assessment for Upper Extremity (FMA-UE).¹⁰ How a hand manipulates an object highly depends on the level of hand function impairment. Investigating hand use in addition to arm use is valuable and provides different information about UL function. In addition to hand use, the role of the more-affected hand is another distinct piece of information about hand function during bilateral activities. The role of a hand, as defined in the Chedoke Arm and Hand Activity Inventory (CAHAI),¹¹ can consist of stabilization or manipulation. All aspects of UL use may depend on impairment level,^6,12 the environment in which it is observed,^12-14 and whether the dominant hand is affected.¹⁵ These factors call for ecologically valid assessment of hand use and hand role in real-world conditions.

Wearable technologies that have previously been applied to capture UL use include accelerometers,^16-19 magnetometers,^20,21 force myography,^22,23 and wearable cameras.^7,24 Finger-worn accelerometers and magnetometers capture hand movements, but may interfere with a stroke survivor’s naturalistic movements during activities, and the functional interpretation of finger movements is not trivial.²¹ In addition, wrist-worn accelerometers cannot distinguish functional movements using a threshold due to the heterogeneity of the more-affected limb movements after stroke.^19,25 Wrist-worn force myography has been applied to detect reach-to-grasp movements in the community and the reported hand use ratios were approximately 0.3 for stroke survivors and 0.7 for healthy individuals.²³ Hand use ratio from finger-worn accelerometers in a laboratory setting has been reported to have significant correlations with the MAL, the Functional Ability Scale, and the FMA-UE.⁸ Despite the high correlation between hand use ratio and clinical UL assessments, additional details are limited due to the lack of studies describing the hand use ratios of community-dwelling stroke survivors. As for hand role, stroke survivors with severe hand function impairment reported in a survey that they were more likely to use their more-affected hand in tasks where it served as a stabilizer; in contrast, respondents with mild impairment reported a greater likelihood to use their more-affected hands in tasks where it would act as a manipulator.¹¹ No data about measured hand role ratios have been reported, yet this information may be beneficial to quantify performance differences between the 2 hands. Wearable cameras (egocentric video) can record hand movements in context without interfering with the naturalistic movements during activities, and hand use can be identified from the recorded videos using computer vision.^26,27 Video data contains information about hand grasp type, compensatory movements, environment facilitators or barriers, and objects involved in a task, which are relevant to interpreting the functional intent of the movement. The rich content of egocentric video is foreseen to provide additional information compared to motion-based sensors, and the potential benefits of this sensor modality for measuring hand use and hand roles warrant investigation. Therefore, egocentric video was chosen to capture hand function performance in this study. To date, the hand use and hand role ratios extracted from egocentric videos of community-dwelling stroke survivors have not been reported and validated against standardized clinical UL assessments. The aim of this study was to validate the hand use ratio and the hand role ratio of stroke survivors in the community.

 

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