Changes in Unimanual and Bimanual Upper Extremity Use During the Subacute Phase Post-Stroke Assessed in Supervised and Unsupervised Contexts

Abstract

Background:

The subacute phase post-stroke is a critical period for recovery, yet it remains unclear how spontaneous use of the paretic upper extremity (UE) increases during this period.

Objective:

This longitudinal study aimed to characterize changes in patterns of UE use during the subacute phase, focusing on unimanual and bimanual use, and to examine the influence of different clinical contexts on UE use.

Methods:

Participants (n = 41; 28.4 [8.0] days since stroke) were assessed at admission to inpatient rehabilitation, prior to discharge, and at 6 months post-stroke. UE use was measured with wrist-worn accelerometers over 7 consecutive days in 3 contexts: daily life, therapy sessions, and functional assessments. Metrics included the use ratio (UR; paretic/non-paretic) and the percentage of unimanual and bimanual use.

Results:

UR improved from admission to discharge (P < .001), reflecting a more symmetrical UE use, but no further change was observed after discharge (P = .09). Percentage of unimanual non-paretic use decreased while bimanual use increased across all time points (P ≤ .03). Percentage of unimanual paretic use remained low, with no change over time (P = .28). An effect of context was observed for all variables (P ≤ .003), showing more asymmetric UE use outside of supervised clinical contexts (therapies and assessments).

Conclusions:

The subacute phase is characterized by substantial improvements in bimanual UE use during rehabilitation, followed by subtler changes in UE use patterns during the late subacute phase. The discrepancy between UE use during supervised clinical contexts and spontaneous use in daily life highlights the need for accelerometry-based monitoring in clinical practice.

Keywords

stroke rehabilitation upper limb accelerometry activities of daily living recovery of function

Introduction

The subacute phase post-stroke is defined as the period from 1 week to 6 months after stroke onset.¹ This period represents a critical window for neuroplasticity, and rehabilitation during this period can significantly reduce upper extremity (UE) impairments.² However, it remains unclear how spontaneous use of the paretic UE increases during this period. While a number of studies have reported significant improvement in UE use during the subacute phase,^3-5 others have reported no significant change despite ongoing recovery of impairments.^6-8

Wrist-worn accelerometers offer a valid and objective method to measure UE use in everyday life.⁹ They allow to capture performance-level behavior, reflecting what individuals actually do in their daily environment.¹⁰ Metrics derived from accelerometry data, such as the duration of paretic UE use or the ratio of use between paretic and non-paretic UE, are often employed to assess longitudinal changes.^3-5,7 However, these metrics do not provide information on how each UE is used in relation to the other. This is relevant because individuals with chronic stroke exhibit distinct patterns of UE use compared to neurologically intact individuals, with a high proportion of unimanual use of the non-paretic UE and most paretic UE activity occurring during bimanual tasks.^11-14 Evidence shows that UE use pattern affects performance in activities of daily living (ADL): people who use a bimanual strategy rather than relying only on the non-paretic UE shows better functional outcomes.¹⁵ However, existing research on UE use patterns has largely been cross-sectional and focused on either the acute¹⁶ or chronic phases.^11-15

To date, only 1 study has investigated longitudinal changes in unimanual and bimanual patterns of use during the first-year post-stroke.⁵ That study reported improvements in duration of paretic UE use in both unimanual and bimanual contexts during inpatients rehabilitation, but without further gains after discharge. However, their analyses relied on absolute intensity or duration metrics (ie, counts or minutes of unimanual and bimanual use), which are vulnerable to confounding by changes in physical activity.¹⁷ Moreover, they did not report unimanual use of the non-paretic UE, which is essential for characterizing compensatory patterns. Therefore, further studies assessing patterns of UE use throughout the subacute phase are needed to fully characterize how stroke survivors compensate for hemiparesis.

When examining UE use in the subacute phase, environmental and contextual factors must be considered. The rehabilitation setting is unique and can strongly influence UE use, as patients spend substantial time in therapy sessions under clinician supervision.^18,19 It is therefore important to distinguish between spontaneous unsupervised daily UE use and the more constrained, therapist-guided, use of the paretic UE during rehabilitation. A recent scoping review on potential modifying factors of UE use highlighted that these environmental and contextual factors remain underexplored.²⁰ Filling this gap is critical because understanding how UE use varies across contexts, such as therapy sessions or functional task assessments, can help determine whether behaviors observed in clinical setting accurately reflect patients’ behavior during everyday activities.

Therefore, this study had 2 objectives: (1) to characterize changes in patterns of UE use during the subacute phase post-stroke, with a focus on unimanual versus bimanual use; (2) to examine the influence of different contexts (daily use vs therapies and assessments) on UE use. We hypothesized that most changes in UE use patterns would occur during the early subacute phase and that unsupervised contexts would elicit higher levels of unimanual non-paretic UE use.

Methods

This was a longitudinal prospective cohort study of subacute stroke patients investigating UE use as assessed by accelerometers. The study was approved by the hospital ethic board (CIUSSS-CN, #2022-2550), and all participants provided their written inform consent.

Admissions in a Canadian stroke rehabilitation unit at the Quebec Physical Rehabilitation Institute were systematically screened for eligibility between May 2022 and December 2024. Participants were approached to participate if they met the following inclusion criteria: (1) diagnosis of ischemic or hemorrhagic stroke confirmed by a neurologist; (2) less than 6 weeks post-stroke at the time of consent; (3) hemiparesis affecting the UE. Exclusion criteria were: (1) inability to follow verbal commands; (2) history of prior symptomatic stroke or other neurological disorders; and (4) pre-existing musculoskeletal condition affecting the UE.

Clinical and demographic information were extracted from patients’ medical record to characterize the sample. Cognitive status was assessed using the Montreal Cognitive Assessment (MoCA) and was administered by the unit’s neuropsychologist upon admission.²¹ Walking independence was assessed using the Chedoke-McMaster Stroke Assessment (CMSA) by physiotherapists at admission and discharge from rehabilitation.

Procedure

UE use was measured with wrist-worn accelerometers (ActiGraph GT3X, ActiGraph LLC, Pensacola, FL). Participants wore the accelerometers on both wrists for 7 consecutive days at 3 time points: (1) upon admission to the stroke rehabilitation unit; (2) 6 week later, prior to discharge; (3) at 6 months post-stroke. Participants were instructed to always wear the accelerometers during each week of monitoring, removing them only during hygiene. Written instructions and a visual reminder were provided and placed at bedside. Instructions were also communicated to the nursing staff and therapists to ensure consistent and accurate wear throughout the monitoring periods. For the 6 months assessment, written instructions with a visual reminder were also provided, and a mid-week phone call was conducted to ensure proper wear.

Acceleration data were recorded on 3 axes at 30 Hz. Raw data were extracted using ActiGraph’s proprietary software ActiLife. Data were subsequently processed using an open-source MATLAB script.²² Visual inspection was performed to identify and exclude periods of sleep, periods of non-wear or instances where only 1 accelerometer was worn for an extended duration. A minimum wear period of 2 complete days was required for inclusion in the analysis. Stroke UE use studies are based on a monitoring period of 1 to 3 days,²³ and physical activity research showed that more than 1 day is necessary for acceptable reliability²⁴ and that 2 wear days is highly correlated to 7 days accelerometry.²⁵ Following the method described in Poitras et al,²⁶ the raw signal was filtered using a continuous eighth-order bandpass filter. The acceleration values were then converted into activity counts (ACs; 0.001664g). These AC were then resampled on 1-second epoch. For each epoch, a vector magnitude (VM) was calculated using Euclidean norm ( $V M = \sqrt{x^{2} + y^{2} + z^{2}}$ ). This yielded a single AC value for each epoch, representing overall movement intensity. Finally, a threshold was applied to the VM value to determine the presence or absence of movement at each epoch. Prior work have shown that the conventional method of using a threshold of 1 AC per epoch tends to overestimate the duration of UE use, whereas higher thresholds provide greater specificity and yield more accurate estimates.²⁷ Following findings of Pohl et al,²⁷ a threshold of 20 AC per second was selected, as it has been shown to provide optimal accuracy for detecting functional movement at the paretic UE. However, the same threshold was applied to both UE rather than using a higher threshold for the non‑paretic side, as proposed by Pohl et al Because the aim of the present study was to characterize patterns of unimanual and bimanual UE use, applying an asymmetric and higher threshold to the non-paretic UE could have biased classification by inflating estimates of unimanual paretic use.

Accelerometry metrics based on duration were selected as they are clinically interpretable. The use ratio (UR) reflected overall symmetry of UE use,⁹ while percentage-based metrics of unimanual and bimanual use allowed to characterize the patterns of use.^13,14,28

UR was calculated by dividing the total duration of paretic UE use by the total duration of non-paretic UE use. It has been validated in stroke populations and is less influenced by variation in overall physical activity compared to other accelerometry metrics.¹⁷ A value of 1 indicates perfect symmetry in UE use and a value approaching zero suggest predominant use of the non-paretic UE.

% unimanual paretic use: total duration of paretic UE use while the non-paretic UE is not moving, divided by the total amount of time where at least 1 UE is moving.

% unimanual non-paretic use: total duration of non-paretic UE use while the paretic UE is not moving, divided by the total amount of time where at least 1 UE is moving.

% bimanual use: total duration where both UE are moving simultaneously, divided by the total amount of time where at least 1 UE is moving.

To explore how contextual factors influence UE use, accelerometry data were collected in 3 distinct contexts: (1) during daily living; (2) during rehabilitation therapies; and (3) during scripted functional tasks in an assessment context. Daily-living metrics were derived from the full 7-day recording, with periods spent in therapy removed to ensure that these values reflected natural, unsupervised movement patterns. To isolate UE use during rehabilitation sessions, occupational and physical therapists completed diaries identifying the start and end times of therapy sessions. These time-stamped entries were then used to segment the accelerometry data using the MATLAB script. A minimum of 2 hours of therapy over the 7‑day monitoring period was required for inclusion in the analysis.

For the accelerometry data collected during scripted functional tasks in an assessment context, the Chedoke Arm and Hand Activity Inventory (CAHAI) was used.²⁹ The CAHAI is a standardized measure of bimanual function and consist of 9 bimanual functional tasks: (1) Open a jar of coffee; (2) Call 911; (3) Draw a line with a ruler; (4) Pour a glass of water; (5) Wring out a washcloth; (6) Do up 5 buttons; (7) Dry back with towel; (8) Put toothpaste on a toothbrush; (9) Cut medium consistency putty with a knife and fork.

Rehabilitation Care

All participants received intensive rehabilitation for at least 6 weeks between the 2 first assessment time points (admission and discharge). Inpatient rehabilitation consisted of 4 one-hour sessions of occupational therapy and 4 one-hour sessions of physical therapy per week. Occupational therapy consisted mostly of functional UE exercise and ADLs training. Physical therapy included mostly upper and lower extremity exercises and walking training. UE exercises in occupational therapy were typically oriented toward functional task-oriented activities aiming both gross and fine motor skills, whereas UE exercises in physiotherapy typically focused on gross motor and strengthening exercises. Additionally, participants with sufficient motricity received a group intervention based on the GRASP 3 times a week for 1 hour. Participant with more severe UE impairment received mirror therapy, 4 times 30 minutes per week. It was ensured that no participant underwent Constraint‑Induced Movement Therapy during the accelerometry monitoring period, as it would have biased spontaneous daily UE use. Speech therapy and neuropsychological follow-ups were not classified as time spent in therapy for the contextual analysis of the accelerometry data.

Analysis

Descriptive statistics were computed to characterize the sample at baseline. To quantify the proportion of participants with asymmetric UE use at each time points, normative reference values from Bailey et al³⁰ were used. The normative value for UR in healthy adults is 0.95 (standard deviation [SD] = 0.06). We determined that a subject with a UR under 0.83 (1.96 SD below the mean) indicate impaired UE use.

To assess changes in UE use over time and across different contexts, linear mixed models were used. Linear mixed models are robust to missing data and allow for modeling individual trajectories while accounting for repeated measures. Considering that we only had 2 assessment times for UE use during therapy (no more rehabilitation at 6 months post-stroke), 2 separate models were made. The first model used a 3 × 2 factorial design, with a 3-level fixed factor for time (admission, discharge, and 6 months post-stroke) and a 2-level fixed factor for context (daily use vs functional assessment). The second model used a 2 × 2 factorial design, with 2 levels for time (admission and discharge) and 2 levels for context (daily use and use during therapy). In both models, a random factor for subject was used to account for inter-individual variability in baseline UE use and progression over time. Separate models were made for each metrics (UR, % unimanual paretic use, % unimanual non-paretic use, and % bimanual use). This resulted in a total of 8 mixed models. Model selection was guided by comparison of covariance structures using Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC), with the best-fitting structure retained for final analysis.³¹ Assumptions of normality were verified by inspecting the distribution of residuals. For post-hoc comparisons, Sidak correction was applied to adjust for multiple testing.

Considering previous studies demonstrating an effect of concordance on UE use (ie, paresis at the dominant hand),²⁰ concordance was assessed by adding a fixed between-subject factor in the previous models.

To ensure comparability with previous studies, sensitivity analyses were conducted using alternative accelerometry processing approaches and metrics. First, analyses were repeated using the same metrics but applying a threshold of 1 AC per 1-second epoch. Second, alternative metrics were examined, including absolute duration of unilateral and bilateral use (ie, before normalizing for total UE use), as well as the Magnitude Ratio, which represents symmetry in UE use intensity.¹²

Results

A total of 41 stroke survivors were recruited and tested at admission on the rehabilitation unit (28.4 ± 8.0 days after stroke). Of the 209 admissions screened, 62 individuals met the eligibility criteria and 41 consented to participate. Participants’ demographic and clinical information are reported in Table 1. Clinical information related to mobility are reported in Supplemental Materials (Supplemental Table S1). The sample size decreased to 39 participants at discharge, and to 33 at 6 months post stroke. Reason for dropout included voluntary withdrawal (n = 3), palliative care (n = 2), recurrent stroke (n = 1), distance constraint (n = 1), and inability to contact (n = 1). Participants who dropped out did not differ significantly from those who completed the study in any clinical or demographic characteristic. Characteristics of participants who dropped out are presented in Table S2 in Supplemental Materials.

Table 1.

Demographic and Clinical Information (n = 41).

Variable	Mean (SD)
Age	64.6 (14.4)
Time since stroke (days)
Admission (n = 41)	28.4 (8.0)
Discharge (n = 39)	68.0 (10.9)
6 months (n = 33)	207.2 (25.0)
Days in rehabilitation	60.8 (25.8)
CAHAI at admission	33.5 (18.1)
MoCA	23.0 (4.2)
	n (%)
Gender (male/female)	26/15 (63/37)
Side of lesion (right/left)	24/17 (58/42)
Type of stroke (Isch/Hem)	31/10 (76/24)
Dominant hand affected (yes/no)	17/24 (42/58)

Abbreviations: CAHAI, Chedoke Arm and Hand Activity Inventory, range 9 to 63; Hem, Hemorrhagic Stroke; Isch, Ischemic Stroke; MoCA, Montreal Cognitive Assessment, range 0 to 30.

The average accelerometer wear time was 88.0 ± 14.3 hours at admission, 85.5 ± 20.7 hours at discharge and 84.5 ± 22.5 hours at 6 months post-stroke, corresponding approximately to 12 hours of wear per day over 7 consecutive days. All participants had accelerometer data available for a minimum of 2 complete days, and 94.6% of the 111 datasets collected across the 3 assessment periods included data for 5 or more days. Recording during therapies were available for all 41 participants at admission, with an average recording time of 7.5 ± 2.1 hours. At discharge, accelerometry data during therapies was available for 32 participants, with an average recording time of 7.7 ± 3.3 hours. Recording during functional assessment was available for all participants and the average duration was of 12.7 ± 2.9, 12.3 ± 2.8, and 10.2 ± 2.8 minutes at admission, discharge, and 6 months post-stroke, respectively.

Changes in Daily UE Use

At admission, 36 out of 41 subjects (88%) had an asymmetric UE use (UR < 0.83). Six weeks later, 26 out of 38 subjects (68%) still had an asymmetric UE use. At 6 months post-stroke, 21 out of 32 (66%) still exhibited an asymmetric use. Thus, only 34% of the cohort achieved normal symmetry in UE use when attaining the chronic phase.

As for the pattern of use, unimanual use of the non-paretic UE was the most frequent pattern observed at admission, representing 56.8% of the total UE use. At discharge, a more mixed pattern was observed with similar proportion of non-paretic unimanual use and bimanual use (43.6% and 41.7%, respectively). At 6 months post-stroke, bimanual use was slightly more predominant, with 44.3% of the total UE movements, compared to 39.3% of unimanual non-paretic UE use. At all time points, unimanual use of the paretic UE was low, ranging from 14.0% to 16.5% of total UE movements. Refer to Table 2 to see estimated marginal means and standard errors for each metric at the different time points and in different contexts.

Table 2.

Accelerometry Data.

Variable	Admission	Discharge	6 months
Daily use
Use ratio	0.53 (0.04)	0.69 (0.05)	0.75 (0.05)
% unimanual paretic	14.0 (1.3)	14.5 (1.3)	16.5 (1.4)
% unimanual non-paretic	56.8 (3.2)	43.6 (3.3)	39.3 (3.4)
% bimanual	29.3 (2.4)	41.7 (2.5)	44.3 (2.6)
Therapy
Use ratio	0.77 (0.05)	0.93 (0.05)
% unimanual paretic	22.0 (1.6)	24.9 (1.7)
% unimanual non-paretic	43.2 (2.8)	32.5 (2.9)
% bimanual	34.8 (1.9)	42.4 (2.0)
Functional assessment
Use ratio	0.64 (0.04)	0.76 (0.05)	0.81 (0.05)
% unimanual paretic	12.3 (1.3)	13.3 (1.3)	12.0 (1.4)
% unimanual non-paretic	46.2 (3.2)	36.1 (3.3)	30.0 (3.4)
% bimanual	41.4 (2.5)	50.6 (2.5)	58.1 (2.6)

Based on Marginal Estimated Means and standard errors from the linear mixed models.

An AR(1) covariance model was used for all linear mixed models considering it allowed a normal distribution of the residuals and produced the lowest AIC and BIC.

Daily Use and Use During Functional Assessment From Admission to 6 Months Post-Stroke

Changes in accelerometry variables over time during daily use and during functional assessment are shown in Figure 1. See Table 3 for statistics related to the linear mixed models. Individual trajectories for the daily use context are shown in Supplemental Materials (Figure S1).

Figure 1.

Changes in daily use and use during functional assessment. Circles with solid lines represent daily use, while squares with dashed lines indicate use during functional assessment. Data represent estimated marginal means and standard errors derived from linear mixed models.

Table 3.

Statistics of the Linear Mixed Models for Daily Use and Use During Functional Assessment.

	Factor	Use ratio			Unimanual paretic
Effect type	Factor	Df	F	P	Df	F	P
Main effect	Time	2, 87	31.4	<.001	2, 102	1.3	.283
Main effect	Context	1, 81	18.3	<.001	1, 61	9.5	.003
Interaction	Time × context	2, 159	0.90	.411	2, 160	2.1	.122
Post-Hoc	Time 1-2			<.001			NA
	Time 1-3			<.001			NA
	Time 2-3			.092			NA
		Unimanual non-paretic			Bimanual
Effect type	Factor	Df	F	P	Df	F	P
Main effect	Time	2, 89	37.4	<.001	2, 102	51.0	<.001
Main effect	Context	1, 92	47.7	<.001	1, 76	66.5	<.001
Interaction	Time × context	2, 160	0.4	.650	2, 161	1.1	.346
Post-Hoc	Time 1-2			<.001			<.001
	Time 1-3			<.001			<.001
	Time 2-3			.031			.010

Abbreviations: Df, degrees of freedom; F, F-statistic; P, P-value; NA, not applicable.

A significant effect of time was observed for the UR, % unimanual non-paretic use and % bimanual use (P < .001), but not for the % unimanual paretic use (P = .283). Post-hoc analysis showed that most of the change in the UR were observed between admission and discharge (P < .001), with no significant change between discharge and 6 months post-stroke. Percentage of non-paretic unimanual use decreased between admission and discharge (P < .001) and continued to decrease after discharge (P = .03). Percentage of bimanual use increased from admission to discharge (P < .001) and continued to improve after discharge (P = .01).

A significant effect of context was observed for all variables (P ≤ .003). Both UR and % bimanual use were higher during the functional assessment than during daily spontaneous use, while the reverse was observed for % unimanual use for both the paretic and non-paretic UE. No interaction between time and context were observed for any variables.

Post hoc analyses examined whether rehabilitation duration (45% of participants received ≥2 weeks after discharge) and variability in time post-stroke at assessment influenced UE use outcomes. Each factor was entered separately as a covariate in the original linear mixed models. Rehabilitation duration was not a significant covariate (P = .80-.96) and controlling for time post-stroke at assessments did not change the main effects of Time or Context for any UE use metric.

Use Inside and Outside Therapy From Admission to Discharge

Changes in accelerometry variables over time during daily use and during therapy sessions are shown on Figure 2. See Table 4 for statistics related to the linear mixed models.

Figure 2.

Changes in daily use and use during therapies. Circles with solid lines represent daily use, while squares with dashed lines indicate use during therapies. Data represent estimated marginal means and standard errors derived from linear mixed models.

Table 4.

Statistics of the Linear Mixed Models for Use Inside and Outside Therapy.

	Factor	Use ratio			Unimanual paretic
Effect type	Factor	Df	F	P	Df	F	P
Main effect	Time	1, 47	21.2	<.001	1, 44	1.9	.180
Main effect	Context	1, 79	78.9	<.001	1, 71	72.6	<.001
Interaction	Time × context	1, 108	0.0	.997	1, 109	0.9	.353
		Unimanual non-paretic			Bimanual
Effect type	Factor	Df	F	P	Df	F	P
Main effect	Time	1, 44	53.1	<.001	1, 50	58.0	<.001
Main effect	Context	1, 71	90.0	<.001	1, 71	8.3	.005
Interaction	Time × context	1, 108	0.6	.437	1, 108	3.8	.054

Abbreviations: Df, degrees of freedom; F, I-statistic; P, P-value; NA, not applicable.

A significant effect of time was observed for the UR, % unimanual non-paretic use and % bimanual use (P < .001), but not for the % unimanual paretic use (P = .180). A significant effect of context was observed for all variables (P ≤ .005): UR, % unimanual paretic use and % bimanual use were higher during therapy than during daily spontaneous use, while the reverse was observed for % unimanual non-paretic use.

No significant effect of concordance was observed for any accelerometry metric when added as a between-subject factor in the linear mixed models of either context comparison (P = .17-.98).

Sensitivity Analyses

Sensitivity analyses to explore the effect of threshold selection are presented in Supplemental Materials. The 20 AC threshold yielded smaller UR, lower proportion of bimanual use, and higher proportion of unimanual use (Supplemental Figure S2, Supplemental Table S3). However, results from the linear mixed models were largely consistent when using an AC threshold of 1 or 20 (Supplemental Table S4). Sensitivity analyses looking at metrics of absolute duration of unilateral and bilateral UE use are presented in Supplemental Materials (Supplemental Tables S5-S7). Similar results were obtained in regard of bimanual use and unimanual non-paretic use. However, a significant effect of Time was observed in duration of unimanual paretic use. Analyses of the Magnitude Ratio yielded results consistent with those observed for the UR (Supplemental Tables S8-S10).

Discussion

Changes in Daily UE Use Over Time

The primary objective of this study was to characterize changes in UE use patterns during the subacute phase following stroke. Our findings indicate an increase in symmetry in UE use, accompanied by a decrease in unimanual non-paretic use and an increase in bimanual use over time. However, unimanual use of the paretic UE remained low and showed no significant improvement throughout the subacute phase.

Previous studies monitoring UE use in the early subacute phase have reported mixed results, including no change in UE use during rehabilitation,⁸ an early plateau around 3 to 6 weeks post-stroke³² and gains throughout the early subacute phase.^3-5 The conflicting results could be explained by differences in follow-up periods, rehabilitation duration, and accelerometry methods. Our results showed that most improvements occurred during the rehabilitation period, with substantial changes in the UR, unimanual non-paretic use, and bimanual use between approximately 4- and 10-weeks post-stroke. This confirms that significant changes in UE use can occur across the full span of the early subacute phase.

Importantly, we also observed modest but significant improvements in UE use patterns in the late subacute phase, as evidenced by a decrease in unimanual non-paretic use and an increase in bimanual use between discharge and 6 months post-stroke. A trend toward improvement in UR during this period was also observed but did not reach statistical significance, which may partly reflect a ceiling effect, as one third of participants had already achieved a normal UR at discharge. These findings challenge previous reports suggesting that no significant changes in UE use occur after discharge from rehabilitation and during the late subacute phase.^3-7,32 The prolonged gains observed in our cohort may be explained by the extended rehabilitation care that some participants received after the discharge assessments. However, post-hoc analysis exploring the impact of rehabilitation duration on UE use outcomes showed no significant effect. Differences in accelerometry methods may also contribute, as longitudinal analysis of unimanual and bimanual use percentages has not previously been reported in subacute stroke, and the change between discharge and 6 months post-stroke was no longer significant when a lower AC threshold was used in sensitivity analyses.

There is a clear potential for improving UE use beyond the early subacute phase. Improvement in UE capacity in the late subacute period, without corresponding changes in use, have been repeatedly documented, suggesting an unexploited potential for improved use.^3,6-7 Moreover, it has been showed that improvement in UE use is possible even in the chronic phase when providing home-based rehabilitation^33,34 or intensive in-clinic rehabilitation.^35,36 This aligns with evidence that structural brain remodeling can persist beyond the subacute phase³⁷ and that prolonged intensive rehabilitation can leverage remaining neuroplasticity to support further recovery.^38,39 Enhancing the continuum of care after discharge with accessible interventions like home-based therapy³³ or sensor-based feedback systems³⁴ could allow improvement in UE use and autonomy in daily living beyond the traditional rehabilitation window.

Patterns of UE Use

A shift in UE use patterns was also observed during the subacute phase. At admission, stroke survivors predominantly relied on unimanual use of the non-paretic UE when outside of the rehabilitation sessions. By discharge, they gradually transitioned toward a mixed strategy of unimanual non-paretic and bimanual use, which consolidated toward a slightly more prevalent bimanual strategy at 6 months post-stroke. Unimanual use of the paretic UE remained minimal through all the subacute period.

These findings are aligned with previous cross-sectional studies in the acute and chronic phases post-stroke. During the acute phase, compensation typically involves increased unimanual use of the non-paretic UE, with a proportion of 51% of total UE movements.¹⁶ Our findings showed that this strategy was maintained in the first weeks post-stroke, with a similar proportion of 57% unimanual non-paretic UE use at admission on the stroke unit. During the chronic phase, cross-sectional studies reported minimal unimanual use of the paretic UE and high proportion of bimanual use ranging from 49% to 52% of total UE use,^12-14 similar to the 44% bimanual use observed in our cohort at 6 months post-stroke. However, these values remain below those observed in neurologically intact adults, with bimanual UE use reaching 67%.¹²

Despite the overall increase in bimanual use, we did not observe changes in proportion of unimanual use of the paretic UE over time. However, sensitivity analysis using metrics of absolute duration of use revealed a significant increase in duration of unimanual use of the paretic UE between admission and discharge. Similar findings have been reported in a study in subacute stroke showing a small but significant increase in absolute duration of unimanual paretic use during rehabilitation.⁵ This likely reflects increased overall activity levels rather than a true change in UE use patterns, as the proportion remained stable.

The combination of high proportion of bimanual use and low unimanual paretic use could be explained by the role of the paretic UE after stroke, which will be mostly used as a stabilizer in bimanual tasks. This hypothesis is corroborated by previous accelerometer studies showing that even when the paretic UE is used bimanually, the intensity of use of the paretic UE is lower than that of the non-paretic UE^11,14 and by a study with ecological observations of ADLs showing that the paretic UE is predominantly employed for stabilization.⁴⁰ This suggest that the observed changes in UE use patterns may partially reflect learning and reinforcement of compensatory strategies, and should not be interpreted as evidence of impairment-level recovery.

Considering the high proportion of bimanual UE use in both stroke survivors and neurologically intact adults, and that the use of a bimanual strategy has been shown to be associated with better function after stroke,¹⁵ there is a strong rationale to consider bimanual functions in both assessments and interventions during rehabilitation. Assessments of bimanual functions, like the CAHAI, have been shown to be an excellent indicator of UE use after stroke.⁴¹ Superiority of bilateral UE training over unilateral and conventional rehabilitation to improve UE capacity is still uncertain.^42-45 However, the effect of bilateral training on UE use has been scarcely studied. Nevertheless, 1 study showed that occupation-based bilateral UE training significantly improved paretic UE use in chronic stroke.³⁶

Influence of Context on UE Use

The second objective of this study was to explore how different contexts influence patterns of UE use and their change over time. We found significant differences in the pattern of UE use in therapy and in functional assessment when compared to spontaneous daily use. Spontaneous daily use was characterized by a lower UR, a higher unimanual use of the non-paretic UE and lower bimanual use. This suggests that outside of structured therapeutic environments, stroke survivors tend to rely more heavily on compensatory strategies involving the non-paretic UE. Those findings are consistent with previous studies that found a higher UR during occupational and physical therapy compared to outside therapy,¹⁹ and lower UR during weekends than weekdays.¹⁸ Such results suggest an influence of environmental and contextual factors in shaping UE use patterns.

Several factors could account for those differences in UE use between contexts. A previous study showed that the mere presence of another person can positively influence the use of the paretic UE, and that self-confidence is linked to improved UE use.⁴⁶ Therefore, the presence of the therapist could improve UE use simply by creating a contextual cue, possibly by the form of a social expectation, or by increasing the patient self-confidence by exploring strategy to incorporate the paretic UE in ADLs and by offering external motivation and reinforcement. The lower UE use in daily use could also be explained by the presence of learned non-use, where individuals suppress the use of their paretic UE due to repeated failures or inefficiencies, even when residuals capacities allowing its use are present.⁴⁷ This behavior may be limited during therapy due to encouragement and structured opportunities to successfully engage the paretic UE. On the contrary, some studies have proposed the presence of a certain threshold in capacity that must be reached before the paretic UE is spontaneously incorporated into daily activities; until this threshold is met, individuals may decide not to use the paretic UE outside therapy for efficiency and ease.^46,48,49 Together, these factors highlight the complex interplay between individual capacity, environmental context, and behavioral conditioning in shaping UE use post-stroke.

This discrepancy between what is observed by the therapist and what happen outside of the clinical setting also underscores the challenge of detecting learned non-use, which tends to manifest outside the therapist’s view. For instance, the mean UR during therapy at discharge closely matched that of neurologically intact adults, potentially giving the impression of near-complete recovery.¹² Yet, a significantly lower UR was observed in daily use. Additionally, patterns of use differed substantially between contexts. Considering the discrepancy in UE use between contexts, accelerometers could serve as valuable tools for clinicians to detect learned non-use in real-world contexts.

Strengths and Limitations

A strength of our study is that we used a 7-day monitoring period, as most other accelerometry’s studies are limited to a 1 to 3 days period.²³ A complete week of monitoring is recommended for accelerometry measures in the physical activity literature, since activity and routines can change significantly from 1 day of the week to another.⁵⁰ Moreover, encompassing both weekdays and weekends is also important as it have been showed that symmetry in UE use change between those 2 periods during rehabilitations.¹⁸

The main limitations of this study are related to the use of accelerometer to assess UE use. Accelerometer-derived metrics are decontextualized, and epochs identified as showing UE movements do not necessarily reflect functional UE use. Bimanual use identified with this method may include UE movements during walking, or non-functional co-occurring contralateral UE movements, and therefore may not represent coordinated bimanual functional activities. Conversely, bimanual activities in which 1 UE serve as a stabilizer may be underreported.

Change detected in UE use can be influenced by change in level of physical activity.¹⁷ This influence is plausible in our cohort, as substantial improvements in mobility were observed during rehabilitation (Supplemental Table S1). However, metrics like the UR and proportion in percentage are less influenced by change in physical activity as they account for the total amount of movement.^17,51 Moreover, accelerometry data collected in the functional assessment context were largely free from common confounders of real-world monitoring, such as whole-body movement, walking, and between-assessment fluctuations in physical activity. The similar improvement trajectories in this controlled context and in real-world monitoring (absence of a Time × Context interaction) suggests that improvements observed in daily life reflect genuine changes in UE use. Future studies could improve measurement validity by adopting multi-sensor approaches to identify and exclude walking periods, or machine-learning–based algorithms to better distinguish functional from non-functional UE movements.^17,52

Other accelerometry-based metrics described in the literature may have provided complementary insights into UE use patterns (for a review on these metrics, see Bernaldo de Quirós et al⁵³). Nevertheless, the UR selected in our study has been shown to be highly correlated with metrics of paretic UE intensity, such as paretic median acceleration and paretic acceleration variability.⁵⁴

Conclusion

Our findings suggest a trajectory of change characterized by substantial improvement in UE use during rehabilitation, followed by subtle changes in use patterns during the late subacute phase. At admission, compensation through unimanual use of the non-paretic UE was predominant, gradually evolving toward a mixed strategy of bimanual and unimanual non-paretic use over time.

A clear discrepancy is observed between UE use during supervised clinical contexts and spontaneous use in daily life during the subacute phase. This finding is critical, as it underscores the importance of monitoring UE during daily life, offering clinicians insights into frequency and patterns of use. Integrating accelerometers into clinical practice could help bridge the gap between observed capacity in therapy and actual functional use in daily life.

Supplemental Material

sj-docx-1-nnr-10.1177_15459683261454938 – Supplemental material for Changes in Unimanual and Bimanual Upper Extremity Use During the Subacute Phase Post-Stroke Assessed in Supervised and Unsupervised Contexts

Supplemental material, sj-docx-1-nnr-10.1177_15459683261454938 for Changes in Unimanual and Bimanual Upper Extremity Use During the Subacute Phase Post-Stroke Assessed in Supervised and Unsupervised Contexts by Léandre Gagné-Pelletier, Isabelle Poitras, Marc Roig and Catherine Mercier in Neurorehabilitation and Neural Repair

Footnotes

Acknowledgements

The authors would like to thank Carole Rigourd for her valuable assistance in developing the MATLAB script for the processing of the accelerometry data. We also thank Marilie Grondin-Soucy for her help in the processing of the accelerometry data.

ORCID iDs

Léandre Gagné-Pelletier

Isabelle Poitras

Marc Roig

Catherine Mercier

Ethical Considerations

This study was approved by the Ethics Committee of the Centre Intégré Universitaire de Santé et de Services Sociaux de la Capitale Nationale (Ethics Code: 2022-2550) on April 12, 2022. This research was conducted ethically in accordance with the World Medical Association Declaration of Helsinki.

Consent to Participate

All participants provided written informed consent prior to enrolment in the study.

Author Contributions

Léandre Gagné-Pelletier: Conceptualization; Data curation; Formal analysis; Investigation; Methodology; Project administration; and Writing—original draft. Isabelle Poitras: Conceptualization; Methodology; Software; and Writing—review & editing. Marc Roig: Conceptualization; Methodology; and Writing—review & editing. Catherine Mercier: Conceptualization; Funding acquisition; Methodology; Resources; Supervision; and Writing—review & editing.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was funded by a grant from the Fonds de recherche du Québec–Santé [FRQ-S; #251649]. CM holds the Canada Research Chair in Sensorimotor Rehabilitation and Pain and the Université Laval Research Chair in Cerebral Palsy. MR is supported by a Salary Award (Junior II) from FRQ-S. LGP is supported by a Doctoral scholarship from FRQ-S. IP was supported by a fellowship from the Canadian Institutes of Health Research.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Supplementary Material

Supplementary material for this article is available on the Neurorehabilitation & Neural Repair website along with the online version of this article.

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Supplementary Material

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