Three distinct physical behavior types in fatigued patients with multiple sclerosis

Wearable Sensor Technologies to Assess Motor Functions in People With Multiple Sclerosis: Systematic Scoping Review and Perspective

BACKGROUND

Wearable sensor technologies have the potential to improve monitoring in people with multiple sclerosis (MS) and inform timely disease management decisions. Evidence of the utility of wearable sensor technologies in people with MS is accumulating but is generally limited to specific subgroups of patients, clinical or laboratory settings, and functional domains.

OBJECTIVE

This review aims to provide a comprehensive overview of all studies that have used wearable sensors to assess, monitor, and quantify motor function in people with MS during daily activities or in a controlled laboratory setting and to shed light on the technological advances over the past decades.

METHODS

We systematically reviewed studies on wearable sensors to assess the motor performance of people with MS. We scanned PubMed, Scopus, Embase, and Web of Science databases until December 31, 2022, considering search terms "multiple sclerosis" and those associated with wearable technologies and included all studies assessing motor functions. The types of results from relevant studies were systematically mapped into 9 predefined categories (association with clinical scores or other measures; test-retest reliability; group differences, 3 types; responsiveness to change or intervention; and acceptability to study participants), and the reporting quality was determined through 9 questions. We followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) reporting guidelines.

RESULTS

Of the 1251 identified publications, 308 were included: 176 (57.1%) in a real-world context, 107 (34.7%) in a laboratory context, and 25 (8.1%) in a mixed context. Most publications studied physical activity (196/308, 63.6%), followed by gait (81/308, 26.3%), dexterity or tremor (38/308, 12.3%), and balance (34/308, 11%). In the laboratory setting, outcome measures included (in addition to clinical severity scores) 2- and 6-minute walking tests, timed 25-foot walking test, timed up and go, stair climbing, balance tests, and finger-to-nose test, among others. The most popular anatomical landmarks for wearable placement were the waist, wrist, and lower back. Triaxial accelerometers were most commonly used (229/308, 74.4%). A surge in the number of sensors embedded in smartphones and smartwatches has been observed. Overall, the reporting quality was good.

CONCLUSIONS

Continuous monitoring with wearable sensors could optimize the management of people with MS, but some hurdles still exist to full clinical adoption of digital monitoring. Despite a possible publication bias and vast heterogeneity in the outcomes reported, our review provides an overview of the current literature on wearable sensor technologies used for people with MS and highlights shortcomings, such as the lack of harmonization, transparency in reporting methods and results, and limited data availability for the research community. These limitations need to be addressed for the growing implementation of wearable sensor technologies in clinical routine and clinical trials, which is of utmost importance for further progress in clinical research and daily management of people with MS.

TRIAL REGISTRATION

PROSPERO CRD42021243249; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=243249.

Bright light therapy as a non-pharmacological treatment option for multiple sclerosis-related fatigue: A randomized sham-controlled trial

Background

Fatigue is a common symptom in people with multiple sclerosis (pwMS) that significantly impairs quality of life. Bright light therapy may be a cheap treatment option with little to no adverse events.

Objectives

To evaluate the effectiveness of bright light therapy as a treatment option for MS-related fatigue.

Methods

This was randomized sham-controlled trial including 26 pwMS with a Fatigue Severity Scale (FSS) Score ≥36. Participants were assigned to receive either bright white light therapy (n = 13) or dim red light (sham-intervention; n = 13). Participants used the respective intervention for 30 min each morning for two weeks, followed by a two-week washout period. The primary endpoint was the difference in FSS scores following light treatment as calculated by analysis of covariance.

Results

There was no significant difference in FSS (F(1,23) = 2.39, p = .136, partial ⴄ² = .094). However, FSS scores generally improved over the course of the study in a clinically relevant manner.

Conclusion

Bright light therapy decreased FSS scores over the course of this study. However, this effect was not significant in comparison to a sham intervention.

Physical activity dimensions after stroke: patterns and relation with lower limb motor function

Background

Stroke survivors show deteriorated physical functioning and physical activity levels. Physical activity levels of stroke survivors are generally low. It is increasingly recognized that physical activity is a multidimensional construct that cannot be captured in a single outcome. In-depth insight into multidimensional physical activity patterns may guide the development and timing of targeted rehabilitation interventions. This longitudinal cohort study explored how multidimensional physical activity outcomes develop during recovery in the subacute phase after stroke and if changes in physical activity were correlated to recovery of lower limb motor function.

Methods

Patients were recruited during inpatient rehabilitation. At 3, 12, and 26 weeks post-onset, motor function was measured by the Fugl-Meyer Lower Extremity Assessment (FMA-LE). Physical activity was measured with the Activ8 accelerometer in multiple outcomes: counts per minute during walking (CPM_walking; a measure of Intensity), number of active bouts (Frequency), mean length of active bouts (Distribution) and % of waking time in upright positions (Duration). Generalized estimating equations (GEE) were used to study changes in physical activity over time and the relation with the change in lower limb motor recovery.

Results

Thirty-nine patients (age 56 ± 9, 77% male, 89% ischemic stroke) were included. GEE models showed a significant main effect of time for PA Intensity (+ 13%, p = 0.007) and Duration (+ 64%, p = 0.012) between 3 and 12 weeks. Motor function did not show a significant effect in all PA models across the 3 timepoints (p > 0.020). A significant interaction effect of time × motor function was observed (p < 0.001).

Conclusions

Patterns of PA recovery depend on the PA dimensions: PA Intensity and Duration increased mostly between 3 and 12 weeks post-stroke, whereas Frequency and Distribution did not show substantial changes. Further, no strong associations with motor recovery and high inter-individual variability were documented, which underlies the need to consider factors specific to the disease, the individual patient and the context.

Physical activity profiles in Parkinson's disease

Background

Identifying physical activity (PA) profiles of people with Parkinson’s Disease (PD) could provide clinically meaningful knowledge concerning how to tailor PA interventions. Our objectives were therefore to i) identify distinct PA profiles in people with PD based on accelerometer data, ii) explore differences between the profiles regarding personal characteristics and physical function.

Methods

Accelerometer data from 301 participants (43% women, mean age: 71 years) was analysed using latent profile analyses of 15 derived PA variables. Physical function measurements included balance performance, comfortable gait speed and single and dual-task functional mobility.

Results

Three distinct profiles were identified; “Sedentary” (N = 68), “Light Movers” (N = 115), “Steady Movers” (N = 118). “Sedentary” included people with PD with high absolute and relative time spent in Sedentary behaviour (SB), little time light intensity physical activity (LIPA) and negligible moderate-to-vigorous physical activity (MVPA). “Light Movers” were people with PD with values close to the mean for all activity variables. “Steady Movers” spent less time in SB during midday, and more time in LIPA and MVPA throughout the day, compared to the other profiles. “Sedentary” people had poorer balance (P = 0.006), poorer functional mobility (P = 0.027) and were more likely to have fallen previously (P = 0.027), compared to “Light Movers. The Timed Up and Go test, an easily performed clinical test of functional mobility, was the only test that could distinguish between all three profiles.

Conclusion

Distinct PA profiles, with clear differences in how the time awake is spent exist among people with mild-moderate PD.

Intensity of daily physical activity - a key component for improving physical capacity after minor stroke?

PURPOSE

Elucidating the complex interactions between physical activity (PA), a multidimensional concept, and physical capacity (PC) may reveal ways to improve rehabilitation interventions. This cross-sectional study aimed to explore which PA dimensions are related to PC in people after minor stroke.

MATERIALS AND METHODS

Community dwelling individuals >6 months after minor stroke were evaluated with a 10-Meter-Walking-Test (10MWT), Timed-Up & Go, and the Mini Balance Evaluation System Test. The following PA outcomes were measured with an Activ8 accelerometer: counts per minute during walking (CPM_walking; a measure of intensity), number of active bouts (frequency), mean length of active bouts (distribution), and percentage of waking hours in upright positions (duration). Multivariable linear regression models, adjusted for age, sex and BMI, were used to assess the relationships between PC and PA outcomes.

RESULTS

Sixty-nine participants [62.2 ± 9.8 years, 61% male, 20 months post onset (IQR 13.0-53.5)] were included in the analysis. CPM_walking was significantly associated to PC in the 10MWT (std. ß = 0.409, p = 0.002), whereas other associations between PA and PC were not significant.

CONCLUSIONS

The PA dimension intensity of walking is significantly associated with PC, and appears to be an important tool for future interventions in rehabilitation after minor stroke.Implications for rehabilitationIt is recommended to express physical activity after minor stroke in multiple dimensions such as intensity, frequency, duration and distribution.In particular, intensity of physical activity measured with accelerometer counts is most closely related to physical capacity.The findings of this study underline the importance of being physically active beyond a certain intensity.In future development of interventions and guidelines that aim to promote daily physical activity, intensity should be taken into account.

Circadian Activity Rhythm in Early Relapsing-Remitting Multiple Sclerosis

While relapsing-remitting is the most prevalent course of multiple sclerosis, the prognostic/predictive markers of the worsening of symptomatology are still debated. With reference to other diseases, the study of the circadian activity rhythm, according to the theoretical framework of the two-process model of sleep regulation and applying functional linear modeling, proved to be useful to identify a possible marker. The usefulness of the study of circadian activity rhythm in multiple sclerosis is strengthened by recent findings indicating a potential involvement of circadian factors in the multifactorial etiopathology of the disorder. The aim of the present study was to verify whether circadian activity rhythm of early relapsing-remitting multiple sclerosis patients presents specific alterations, through functional linear modeling. Thirty-five relapsing-remitting multiple sclerosis patients (24 females; mean age ± SD = 31.51 ± 7.74) and 35 healthy controls (24 females; mean age ± SD = 31.29 ± 8.02) were enrolled. They wore an actigraph around the non-dominant wrist for one week. Relapsing-remitting multiple sclerosis patients showed a peak in motor activity around 5:00 a.m., higher than that of healthy controls. The timing of the peak in motor activity in the patients could be explained according to the hyperactive hypothalamus-pituitary-adrenal axis and higher cortisol awakening response reported in these patients.