Impact of Moderate Individually Tailored Physical Activity in Multiple Sclerosis Patients with Fatigue on Functional, Cognitive, Emotional State, and Postural Stability

Redlicka, Justyna; Zielińska-Nowak, Ewa; Lipert, Anna; Miller, Elżbieta

doi:10.3390/brainsci11091214

Cited by 5 publications

(4 citation statements)

References 42 publications

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“…The range of the EDSS scale was selected due to the requirements of the study. We also used this range in our earlier study [24]. The patient had to stand up, either alone or with orthopedic assistance, for 2 × 30 s and could move even in a small area.…”

Section: Clinical Scalesmentioning

confidence: 99%

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The Relationship between Cognitive Dysfunction and Postural Stability in Multiple Sclerosis

et al. 2021

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Background and Objectives: Multiple Sclerosis (MS) is a demyelinating disease of the central nervous system (CNS), most commonly characterized by balance dysfunction, fatigue syndrome and cognitive impairment. The goal of our study was to determine the association between cognitive functions and static posture control. Materials and Methods: The research group consisted of 76 randomized MS patients (ICDG 35.0) hospitalized at the Neurological Rehabilitation Clinic of the Medical University of Lodz. This group was divided into three subgroups according to the cognitive assessment based on the Mini Mental State Examination (MMSE) for patients over 65 years of age and the Montreal Cognitive Assessment (MoCA) under the age of 65. Fatigue syndrome was assessed using the Fatigue Severity Scale (FSS), and postural stability using a stabilometric platform. Results: The men demonstrated poorer stabilometric platform measurements than the women. Statistically significant differences were observed between patients without dysfunction and severe cognitive impairment. The results of the stabilometric platform were found to correlate with body mass index in all three groups of patients (Spearman’s test). Conclusions: Body mass index and cognition have impact on postural stability in MS patients with moderate disability and fatigue syndrome.

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Section: Clinical Scalesmentioning

confidence: 99%

“…The patient had to stand up, either alone or with orthopedic assistance, for 2 × 30 s and could move even in a small area. Among researchers, the use of scales to assess cognition by age can be observed [24]. Cognitive functioning was assessed with the MMSE in MS patients over 65 years old and with the MoCA below the age of 65.…”

Section: Clinical Scalesmentioning

confidence: 99%

The Relationship between Cognitive Dysfunction and Postural Stability in Multiple Sclerosis

et al. 2021

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“…These discrepancies in findings, particularly for a symptom with such high incidence and impact on QoL, suggest underlying effect modifiers. One such factor may be patient activity levels, daily exercise has been shown to improve both fatigue and postural stability in PwMS [59]. Further longitudinal monitoring of these symptoms with wearable devices may help elucidate true patterns in symptoms and may indicate potential therapeutic targets.…”

Section: Discussionmentioning

confidence: 99%

Digital Phenotypes of Instability and Fatigue Derived From Daily Standing Transitions in Persons With Multiple Sclerosis

VanDyk

Meyer

DePetrillo

et al. 2023

IEEE Trans. Neural Syst. Rehabil. Eng.

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Impairment in persons with multiple sclerosis (PwMS) can often be attributed to symptoms of motor instability and fatigue. Symptom monitoring and queued interventions often target these symptoms. Clinical metrics are currently limited to objective physician assessments or subjective patient reported measures. Recent research has turned to wearables for improving the objectivity and temporal resolution of assessment. Our group has previously observed wearable assessment of supervised and unsupervised standing transitions to be predictive of fall-risk in PwMS. Here we extend the application of standing transition quantification to longitudinal home monitoring of symptoms. Subjects (N=23) with varying degrees of MS impairment were recruited and monitored with accelerometry for a total of ∼6 weeks each. These data were processed using a preexisting framework, applying a deep learning activity classifier to isolate periods of standing transition from which descriptive features were extracted for analysis. Participants completed daily and biweekly assessments describing their symptoms. From these data, Canonical Correlation Analysis was used to derive digital phenotypes of MS instability and fatigue. We find these phenotypes capable of distinguishing fallers from non-fallers, and further that they demonstrate a capacity to characterize symptoms at both daily and sub-daily resolutions. These results represent promising support for future applications of wearables, which may soon augment or replace current metrics in longitudinal monitoring of PwMS.

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“…These discrepancies in findings, particularly for a symptom with such high incidence and impact on QoL, suggest underlying effect modifiers. One such factor may be patient activity levels, daily exercise has been shown to improve both fatigue and postural stability in PwMS [56]. Another possibility is that body temperature is well known to have an effect on MS symptom severity [57], [58], and exhibits cyclic, quasi-circadian patterns that are influenced by a broad spectrum of internal and external factors difficult to control against in a case-control format [59], [60].…”

Section: Discussionmentioning

confidence: 99%

Digital Phenotypes of Instability and Fatigue Derived from Daily Standing Transitions in Persons with Multiple Sclerosis

VanDyk¹,

Meyer²,

DePetrillo³

et al. 2022

Preprint

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<p>Impairment in persons with multiple sclerosis (PwMS) can often be attributed to symptoms of motor instability and fatigue. Symptom monitoring and queued interventions often target these symptoms. Clinical metrics are currently limited to objective physician assessments or subjective patient reported measures. Recent research has turned to wearables for improving the objectivity and temporal resolution of assessment. Our group has previously observed wearable assessment of supervised and unsupervised standing transitions to be predictive of fall-risk in PwMS. Here we extend the application of standing transition quantification to longitudinal home monitoring of symptoms. Subjects (N=23) with varying degrees of MS impairment were recruited and monitored with accelerometry for a total of ~6 weeks each. These data were processed using a deep learning activity classifier to isolate periods of standing transition from which descriptive features were extracted for analysis. Participants completed daily and biweekly assessments describing their symptoms. From these data, Canonical Correlation Analysis was used to derive digital phenotypes of MS instability and fatigue. We find these phenotypes capable of distinguishing fallers from non-fallers, and further that they demonstrate a capacity to characterize symptoms at both daily and sub-daily resolutions. These results represent promising support for future applications of wearables, which may soon augment or replace current metrics in longitudinal monitoring of PwMS. </p>

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Impact of Moderate Individually Tailored Physical Activity in Multiple Sclerosis Patients with Fatigue on Functional, Cognitive, Emotional State, and Postural Stability

Cited by 5 publications

References 42 publications

The Relationship between Cognitive Dysfunction and Postural Stability in Multiple Sclerosis

The Relationship between Cognitive Dysfunction and Postural Stability in Multiple Sclerosis

Digital Phenotypes of Instability and Fatigue Derived From Daily Standing Transitions in Persons With Multiple Sclerosis

Digital Phenotypes of Instability and Fatigue Derived from Daily Standing Transitions in Persons with Multiple Sclerosis

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