Exploring the feasibility and acceptability of sensor monitoring of gait and falls in the homes of persons with multiple sclerosis

Predicting Multiple Sclerosis Outcomes During the COVID-19 Stay-at-home Period: Observational Study Using Passively Sensed Behaviors and Digital Phenotyping

BACKGROUND

The COVID-19 pandemic has broad negative impact on the physical and mental health of people with chronic neurological disorders such as multiple sclerosis (MS).

OBJECTIVE

We presented a machine learning approach leveraging passive sensor data from smartphones and fitness trackers of people with MS to predict their health outcomes in a natural experiment during a state-mandated stay-at-home period due to a global pandemic.

METHODS

First, we extracted features that capture behavior changes due to the stay-at-home order. Then, we adapted and applied an existing algorithm to these behavior-change features to predict the presence of depression, high global MS symptom burden, severe fatigue, and poor sleep quality during the stay-at-home period.

RESULTS

Using data collected between November 2019 and May 2020, the algorithm detected depression with an accuracy of 82.5% (65% improvement over baseline; F₁-score: 0.84), high global MS symptom burden with an accuracy of 90% (39% improvement over baseline; F₁-score: 0.93), severe fatigue with an accuracy of 75.5% (22% improvement over baseline; F₁-score: 0.80), and poor sleep quality with an accuracy of 84% (28% improvement over baseline; F₁-score: 0.84).

CONCLUSIONS

Our approach could help clinicians better triage patients with MS and potentially other chronic neurological disorders for interventions and aid patient self-monitoring in their own environment, particularly during extraordinarily stressful circumstances such as pandemics, which would cause drastic behavior changes.

Development of a Smart Hallway for Marker-Less Human Foot Tracking and Stride Analysis

Objective: In this research, a marker-less ‘smart hallway’ is proposed where stride parameters are computed as a person walks through an institutional hallway. Stride analysis is a viable tool for identifying mobility changes, classifying abnormal gait, estimating fall risk, monitoring progression of rehabilitation programs, and indicating progression of nervous system related disorders. Methods: Smart hallway was build using multiple Intel RealSense D415 depth cameras. A novel algorithm was developed to track a human foot using combined point cloud data obtained from the smart hallway. A method was implemented to separate the left and right leg point cloud data, then find the average foot dimensions. Foot tracking was achieved by fitting a box with average foot dimensions to the foot, with the box’s base on the foot’s bottom plane. A smart hallway with this novel foot tracking algorithm was tested with 22 able-bodied volunteers by comparing marker-less system stride parameters with Vicon motion analysis output. Results: With smart hallway frame rate at approximately 60fps, temporal stride parameter absolute mean differences were less than 30ms. Random noise around the foot’s point cloud was observed, especially during foot strike phases. This caused errors in medial-lateral axis dependent parameters such as step width and foot angle. Anterior-posterior dependent (stride length, step length) absolute mean differences were less than 25mm. Conclusion: This novel marker-less smart hallway approach delivered promising results for stride analysis with small errors for temporal stride parameters, anterior-posterior stride parameters, and reasonable errors for medial-lateral spatial parameters.

Associations Between Self-Reported Symptoms and Gait Parameters Using In-Home Sensors in Persons With Multiple Sclerosis

BACKGROUND AND PURPOSE

Multiple sclerosis (MS) is a progressive neurological disorder, characterized by exacerbations and remissions, often resulting in disability affecting multiple neurological functions. The purpose of this article was (1) to describe the frequencies of self-reported symptoms in a natural environment and (2) to determine characteristics and associations between self-reported symptoms and home gait parameters (speed, stride time, and stride length) at baseline and at 3 months in patients with MS.

METHODS

Participants completed the self-report MS-Related Symptom Scale to measure symptoms. A three-dimensional depth imaging system (Foresite Healthcare) was used to measure gait parameters in the home environment.

RESULTS

These data show significant correlations between the following symptoms: knee locking or collapsing, difficulty sleeping, depression, and anxiety with decreased number of average walks per day; however, the symptoms including trouble-making toilet: day and difficulty in starting urine were positively correlated with average walks per day. The symptom numbness was significantly correlated with decreased speed and decreased stride length.

DISCUSSION AND CONCLUSIONS

Our findings suggest that certain groups of symptoms were more frequently reported with certain gait parameters (stride time/speed) in persons with MS. Rehabilitation nurses can provide optimal care to prevent future decline in symptoms and gait.

Gait asymmetry, and bilateral coordination of gait during a six-minute walk test in persons with multiple sclerosis

Gait impairments in persons with multiple sclerosis (pwMS) leading to decreased ambulation and reduced walking endurance remain poorly understood. Our objective was to assess gait asymmetry (GA) and bilateral coordination of gait (BCG), among pwMS during the six-minute walk test (6MWT), and determine their association with disease severity. We recruited 92 pwMS (age: 46.6 ± 7.9; 83% females) with a range of clinical disability, who completed the 6MWT wearing gait analysis system. GA was assessed by comparing left and right swing times, and BCG was assessed by the phase coordination index (PCI). Several functional and subjective gait assessments were performed. Results show that gait is more asymmetric and less coordinated as the disease progresses (p < 0.0001). Participants with mild MS showed significantly better BCG as reflected by lower PCI values in comparison to the other two MS severity groups (severe: p = 0.001, moderate: p = 0.02). GA and PCI also deteriorated significantly each minute during the 6MWT (p < 0.0001). GA and PCI (i.e., BCG) show weaker associations with clinical MS status than associations observed between functional and subjective gait assessments and MS status. Similar to other neurological cohorts, GA and PCI may be important parameters to assess and target in interventions among pwMS.

Fall definitions, faller classifications and outcomes used in falls research among people with multiple sclerosis: a systematic review

Purpose: To identify the definitions of a fall, faller classifications and outcomes used in prospectively-recorded falls research among people with Multiple Sclerosis (MS).Methods: A systematic review of peer-reviewed journal articles was conducted using electronic databases. Relevant data were extracted by one reviewer and verified by a second independent reviewer.Results: Twenty-six papers met the inclusion criteria. A relative degree of heterogeneity existed amongst studies for the outcomes of interest to this review. Thirteen different fall definitions were identified. Fourteen different falls outcomes were used across the included studies, with six of these reported by only one study each. Data regarding injurious falls were presented by only eight papers. The majority (n = 17) of papers classified individuals as a faller if they fell at least once.Conclusions: This review highlights the large variation in fall definitions, faller classifications and outcomes used in this research field. This hinders cross-comparison and pooling of data, thereby preventing researchers and clinicians from drawing conclusive findings from existing literature. The creation of an international standard for the definition of a fall, faller classification and falls outcomes would allow for transparent and coordinated falls research for people with MS, facilitating progression in this research field.Implications for rehabilitationFalls are a common occurrence among people with Multiple Sclerosis (MS) resulting in numerous negative consequences.There is large heterogeneity in the definitions, methods and outcomes used in falls research for people with MS.This lack of standardisation prevents the accurate cross-comparison and pooling of data, impeding the identification of falls risk factors and effective falls prevention interventions for people with MS.Consequently, clinicians should interpret the outcomes of falls research for people with MS with caution, particularly when comparing studies regarding falls risk assessments and falls prevention interventions for use in clinical practice.

Impact of delayed treatment on exacerbations of multiple sclerosis among Puerto Rican patients

BACKGROUND

There are limited data on multiple sclerosis (MS) patients in underserved groups, including Puerto Rico. In this study, we analyzed the characteristic of MS symptoms and number of relapses in Puerto Rican patients. We then compare these characteristics with MS patients from the US. The number of MS relapses is highly correlated with the treatment onset and adherence. Patients in Puerto Rico have been experiencing lengthy treatment delay. We will discuss the possible causes of such delay and its impact on MS prognosis.

METHODS

This retrospective cohort study consisted of the evaluation of 325 medical records from MS patients attending the Caribbean Neurological Center from 2014 to 2019. We gathered symptoms and comorbidities data as binary objects. The treatment delay was calculated based on the mean value of days between diagnosis and treatment onset for these groups of patients.

RESULTS

We found that on average, the treatment delay for MS patients in Puerto Rico (PR) to receive their medication was 120 days. The most common MS subtype was relapsing-remitting 72.8%, with a mean of 1.684 relapses per year. Initial symptoms were sensory 54%, visual 33.1%, motor 28.8%, coordination 23.2%, fatigue 9.7%, memory 7.3%, depression 6.5%, urinary 4.9%, gastrointestinal 2.4%, and sexual dysfunction 1.6%. The most common comorbidities were hypertension 18.4%, asthma 13.6%, and thyroid disease 12.8%. When we compared the comorbidities between the two populations, immune thrombocytopenia had the highest percent change with the value of almost 200% (0.001% of US patient vs. 0.8% of Puerto Rican MS patients).

CONCLUSION

Patients from Puerto Rico had a 33% higher relapse rate compared to the one reported for MS patients in the US. This higher rate may be related to the long delay in receiving their medications. They also had a higher rate of complex comorbidities such as immune thrombocytopenia or thyroid disease. Our findings provide a proof of concept that delay in receiving medications can increase the number of relapses and complex comorbidities among MS patients.

"Tipping point" concept analysis in the family caregiving context

AIM

Analyze the concept "tipping point" in the older adult family caregiving context to further knowledge about caregiving families, enhancing transdisciplinary theory, research, and practice.

BACKGROUND

While used commonly in some disciplines, how "tipping point" has been used in health care, generally, and in relation to caregiving families, specifically, is less clear. This project was conducted to offer conceptual clarity to tipping point.

DESIGN

Walker and Avant's framework.

DATA SOURCE

Searches of scholarly literature in PsycINFO, CINAHL, and PubMed using the search term "tipping point" in either title or abstract.

REVIEW METHODS

Definitions used were extracted; instances when the concept was implied but the actual term "tipping point" was not used and contexts where the term was used or implied were identified.

RESULTS

The composite definition of a caregiving tipping point is a seemingly abrupt, severe, and absolute change event involving either the older adult or caregiver(s), or both that indicates a breakdown in the status quo of the caregiving system.

CONCLUSIONS

Transdisciplinary research, care, and policy should treat caregiving families as complex systems, use longitudinal assessments, and include colloquial communication. Early detection of impending tipping points will provide family-centered decisional support and enhance families' quality of life and safety.

Spotlight on postural control in patients with multiple sclerosis

Multiple sclerosis (MS) is a disease that heavily affects postural control, predisposing patients to accidental falls and fall-related injuries, with a relevant burden on their families, health care systems and themselves. Clinical scales aimed to assess balance are easy to administer in daily clinical setting, but suffer from several limitations including their variable execution, subjective judgment in the scoring system, poor performance in identifying patients at higher risk of falls, and statistical concerns mainly related to distribution of their scores. Today we are able to objectively and reliably assess postural control not only with laboratory-grade standard force platform, but also with low-cost systems based on commercial devices that provide acceptable comparability to gold-standard equipment. The sensitivity of measurements derived from force platforms is such that we can detect balance abnormalities even in minimally impaired patients and predict the risk of future accidental falls accurately. By manipulating sensory inputs (dynamic posturography) or by adding a concurrent cognitive task (dual-task paradigm) to the standard postural assessment, we can unmask postural control deficit even in patients at first demyelinating event or in those with a radiologic isolated syndrome. Studies on neuroanatomical correlates support the multifactorial etiology of postural control deficit in MS, with the association with balance impairment being correlated with cerebellum, spinal cord, and highly ordered processing network according to different studies. Postural control deficit can be managed by means of rehabilitation, which is the most important way to improve balance in patients with MS, but there are also suggestions of a beneficial effect of some pharmacologic interventions. On the other hand, it would be useful to pay attention to some drugs that are currently used to manage other symptoms in daily clinical setting because they can further impair postural controls of patients with MS.

A battery-less and wireless wearable sensor system for identifying bed and chair exits in a pilot trial in hospitalized older people

Falls in hospitals are common, therefore strategies to minimize the impact of these events in older patients and needs to be examined. In this pilot study, we investigate a movement monitoring sensor system for identifying bed and chair exits using a wireless wearable sensor worn by hospitalized older patients. We developed a movement monitoring sensor system that recognizes bed and chair exits. The system consists of a machine learning based activity classifier and a bed and chair exit recognition process based on an activity score function. Twenty-six patients, aged 71 to 93 years old, hospitalized in the Geriatric Evaluation and Management Unit participated in the supervised trials. They wore over their attire a battery-less, lightweight and wireless sensor and performed scripted activities such as getting off the bed and chair. We investigated the system performance in recognizing bed and chair exits in hospital rooms where RFID antennas and readers were in place. The system’s acceptability was measured using two surveys with 0–10 likert scales. The first survey measured the change in user perception of the system before and after a trial; the second survey, conducted only at the end of each trial, measured user acceptance of the system based on a multifactor sensor acceptance model. The performance of the system indicated an overall recall of 81.4%, precision of 66.8% and F-score of 72.4% for joint bed and chair exit recognition. Patients demonstrated improved perception of the system after use with overall score change from 7.8 to 9.0 and high acceptance of the system with score ≥ 6.7 for all acceptance factors. The present pilot study suggests the use of wireless wearable sensors is feasible for detecting bed and chair exits in a hospital environment.

Continuous In-Home Symptom and Mobility Measures for Individuals With Multiple Sclerosis: A Case Presentation

Gait impairment represents one of the most common and disabling symptoms of multiple sclerosis (MS). To identify which temporal or spatial parameters of gait could be used as outcome measures in interventional studies of individuals with MS with different levels of disability, we evaluated characteristics of these parameters in a case study of 3 participants with MS, using 1 case as an exemplar and the other participants as validation. A case study of an exemplar participant was conducted with a 67-year-old woman with secondary progressive MS served as exemplar, with 2 other participants (52 and 55 years old) as validation. The primary outcome measures we used were stride time, stride length, gait velocity, and daily symptoms. Stride length and velocity of gait decreased with increasing pain and fatigue. The step time was significantly longer later in the day, whereas the step length remained the same. Stride length and velocity are associated with the level of fatigue and pain, as well as the time of day. These characteristics and parameters of gait need to be considered in future studies of gait in MS, with particular attention to temporality of occurrence in persons with MS.