Well shit, you're not solving stroke at all! You're just documenting hand dysfunction. USELESS! I'd fire everyone involved in this crapola!
Validity of Novel Outcome Measures for Hand Function Performance After Stroke Using Egocentric Video
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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