Fifteen years of wireless sensors for balance assessment in neurological disorders

Balance impairment is a major mechanism behind falling along with environmental hazards. Under physiological conditions, ageing leads to a progressive decline in balance control per se. Moreover, various neurological disorders further increase the risk of falls by deteriorating specific nervous system functions contributing to balance. Over the last 15 years, significant advancements in technology have provided wearable solutions for balance evaluation and the management of postural instability in patients with neurological disorders. This narrative review aims to address the topic of balance and wireless sensors in several neurological disorders, including Alzheimer's disease, Parkinson's disease, multiple sclerosis, stroke, and other neurodegenerative and acute clinical syndromes. The review discusses the physiological and pathophysiological bases of balance in neurological disorders as well as the traditional and innovative instruments currently available for balance assessment. The technical and clinical perspectives of wearable technologies, as well as current challenges in the field of teleneurology, are also examined

Dysregulation of MS risk genes and pathways at distinct stages of disease

OBJECTIVE: To perform systematic transcriptomic analysis of multiple sclerosis (MS) risk genes in peripheral blood mononuclear cells (PBMCs) of subjects with distinct MS stages and describe the pathways characterized by dysregulated gene expressions. METHODS: We monitored gene expression levels in PBMCs from 3 independent cohorts for a total of 297 cases (including clinically isolated syndromes (CIS), relapsing-remitting MS, primary and secondary progressive MS) and 96 healthy controls by distinct microarray platforms and quantitative PCR. Differential expression and pathway analyses for distinct MS stages were defined and validated by literature mining. RESULTS: Genes located in the vicinity of MS risk variants displayed altered expression in peripheral blood at distinct stages of MS compared with the healthy population. The frequency of dysregulation was significantly higher than expected in CIS and progressive forms of MS. Pathway analysis for each MS stage–specific gene list showed that dysregulated genes contributed to pathogenic processes with scientific evidence in MS. CONCLUSIONS: Systematic gene expression analysis in PBMCs highlighted selective dysregulation of MS susceptibility genes playing a role in novel and well-known pathogenic pathways

Automatic assessment of the 2-minute walk distance for remote monitoring of people with multiple sclerosis

The aim of this study was to investigate the feasibility of automatically assessing the 2-Minute Walk Distance (2MWD) for monitoring people with multiple sclerosis (pwMS). For 154 pwMS, MS-related clinical outcomes as well as the 2MWDs as evaluated by clinicians and derived from accelerometer data were collected from a total of 323 periodic clinical visits. Accelerometer data from a wearable device during 100 home-based 2MWD assessments were also acquired. The error in estimating the 2MWD was validated for walk tests performed at hospital, and then the correlation (r) between clinical outcomes and home-based 2MWD assessments was evaluated. Robust performance in estimating the 2MWD from the wearable device was obtained, yielding an error of less than 10% in about two-thirds of clinical visits. Correlation analysis showed that there is a strong association between the actual and the estimated 2MWD obtained either at hospital (r = 0.71) or at home (r = 0.58). Furthermore, the estimated 2MWD exhibits moderate-to-strong correlation with various MS-related clinical outcomes, including disability and fatigue severity scores. Automatic assessment of the 2MWD in pwMS is feasible with the usage of a consumer-friendly wearable device in clinical and non-clinical settings. Wearable devices can also enhance the assessment of MS-related clinical outcomes

Automatic Assessment of the 2-Minute Walk Distance for Remote Monitoring of People with Multiple Sclerosis

The aim of this study was to investigate the feasibility of automatically assessing the 2-Minute Walk Distance (2MWD) for monitoring people with multiple sclerosis (pwMS). For 154 pwMS, MS-related clinical outcomes as well as the 2MWDs as evaluated by clinicians and derived from accelerometer data were collected from a total of 323 periodic clinical visits. Accelerometer data from a wearable device during 100 home-based 2MWD assessments were also acquired. The error in estimating the 2MWD was validated for walk tests performed at hospital, and then the correlation (r) between clinical outcomes and home-based 2MWD assessments was evaluated. Robust performance in estimating the 2MWD from the wearable device was obtained, yielding an error of less than 10% in about two-thirds of clinical visits. Correlation analysis showed that there is a strong association between the actual and the estimated 2MWD obtained either at hospital (r = 0.71) or at home (r = 0.58). Furthermore, the estimated 2MWD exhibits moderate-to-strong correlation with various MS-related clinical outcomes, including disability and fatigue severity scores. Automatic assessment of the 2MWD in pwMS is feasible with the usage of a consumer-friendly wearable device in clinical and non-clinical settings. Wearable devices can also enhance the assessment of MS-related clinical outcomes

Using smartphones and wearable devices to monitor behavioural changes during COVID-19

We aimed to explore the utility of the recently developed open-source mobile health platform RADAR-base as a toolbox to rapidly test the effect and response to NPIs aimed at limiting the spread of COVID-19. We analysed data extracted from smartphone and wearable devices and managed by the RADAR-base from 1062 participants recruited in Italy, Spain, Denmark, the UK, and the Netherlands. We derived nine features on a daily basis including time spent at home, maximum distance travelled from home, maximum number of Bluetooth-enabled nearby devices (as a proxy for physical distancing), step count, average heart rate, sleep duration, bedtime, phone unlock duration, and social app use duration. We performed Kruskal-Wallis tests followed by post-hoc Dunns tests to assess differences in these features among baseline, pre-, and during-lockdown periods. We also studied behavioural differences by age, gender, body mass index (BMI), and educational background. We were able to quantify expected changes in time spent at home, distance travelled, and the number of nearby Bluetooth-enabled devices between pre- and during-lockdown periods. We saw reduced sociality as measured through mobility features, and increased virtual sociality through phone usage. People were more active on their phones, spending more time using social media apps, particularly around major news events. Furthermore, participants had lower heart rate, went to bed later, and slept more. We also found that young people had longer homestay than older people during lockdown and fewer daily steps. Although there was no significant difference between the high and low BMI groups in time spent at home, the low BMI group walked more. RADAR-base can be used to rapidly quantify and provide a holistic view of behavioural changes in response to public health interventions as a result of infectious outbreaks such as COVID-19

The utility of wearable devices in assessing ambulatory impairments of people with multiple sclerosis in free-living conditions

Background and objectives Multiple sclerosis (MS) is a progressive inflammatory and neurodegenerative disease of the central nervous system affecting over 2.5 million people globally. In-clinic six-minute walk test (6MWT) is a widely used objective measure to evaluate the progression of MS. Yet, it has limitations such as the need for a clinical visit and a proper walkway. The widespread use of wearable devices capable of depicting patients’ activity profiles has the potential to assess the level of MS-induced disability in free-living conditions. Methods In this work, we extracted 96 features in different temporal granularities (from minute-level to day-level) from wearable data and explored their utility in estimating 6MWT scores in a European (Italy, Spain, and Denmark) MS cohort of 337 participants over an average of 10 months’ duration. We combined these features with participants’ demographics using three regression models including elastic net, gradient boosted trees and random forest. In addition, we quantified the individual feature's contribution using feature importance in these regression models, linear mixed-effects models, generalized estimating equations, and correlation-based feature selection (CFS). Results The results showed promising estimation performance with R2 of 0.30, which was derived using random forest after CFS. This model was able to distinguish the participants with low disability from those with high disability. Furthermore, we observed that the minute-level (≤ 8 minutes) step count, particularly those capturing the upper end of the step count distribution, had a stronger association with 6MWT. The use of a walking aid was indicative of ambulatory function measured through 6MWT. Conclusions This study demonstrates the utility of wearables devices in assessing ambulatory impairments in people with MS in free-living conditions and provides a basis for future investigation into the clinical relevance

Autonomic response to walk tests is useful for assessing outcome measures in people with multiple sclerosis

Objective: The aim of this study was to evaluate the association between changes in the autonomic control of cardiorespiratory system induced by walk tests and outcome measures in people with Multiple Sclerosis (pwMS).Methods: Electrocardiogram (ECG) recordings of 148 people with Relapsing-Remitting MS (RRMS) and 58 with Secondary Progressive MS (SPMS) were acquired using a wearable device before, during, and after walk test performance from a total of 386 periodical clinical visits. A subset of 90 participants repeated a walk test at home. Various MS-related symptoms, including fatigue, disability, and walking capacity were evaluated at each clinical visit, while heart rate variability (HRV) and ECG-derived respiration (EDR) were analyzed to assess autonomic nervous system (ANS) function. Statistical tests were conducted to assess differences in ANS control between pwMS grouped based on the phenotype or the severity of MS-related symptoms. Furthermore, correlation coefficients (r) were calculated to assess the association between the most significant ANS parameters and MS-outcome measures.Results: People with SPMS, compared to RRMS, reached higher mean heart rate (HRM) values during walk test, and larger sympathovagal balance after test performance. Furthermore, pwMS who were able to adjust their HRM and ventilatory values, such as respiratory rate and standard deviation of the ECG-derived respiration, were associated with better clinical outcomes. Correlation analyses showed weak associations between ANS parameters and clinical outcomes when the Multiple Sclerosis phenotype is not taken into account. Blunted autonomic response, in particular HRM reactivity, was related with worse walking capacity, yielding r = 0.36 r = 0.29 (RRMS) and r > 0.5 (SPMS). A positive strong correlation r > 0.7 r > 0.65 between cardiorespiratory parameters derived at hospital and at home was also found.Conclusion: Autonomic function, as measured by HRV, differs according to MS phenotype. Autonomic response to walk tests may be useful for assessing clinical outcomes, mainly in the progressive stage of MS. Participants with larger changes in HRM are able to walk longer distance, while reduced ventilatory function during and after walk test performance is associated with higher fatigue and disability severity scores. Monitoring of disorder severity could also be feasible using ECG-derived cardiac and respiratory parameters recorded with a wearable device at home

The Danger of Walking with Socks: Evidence from Kinematic Analysis in People with Progressive Multiple Sclerosis

Multiple sclerosis (MS) is characterized by gait impairments and severely impacts the quality of life. Technological advances in biomechanics offer objective assessments of gait disabilities in clinical settings. Here we employed wearable sensors to measure electromyography (EMG) and body acceleration during walking and to quantify the altered gait pattern between people with progressive MS (PwPMS) and healthy controls (HCs). Forty consecutive patients attending our department as in-patients were examined together with fifteen healthy controls. All subjects performed the timed 10 min walking test (T10MW) using a wearable accelerator and 8 electrodes attached to bilateral thighs and legs so that body acceleration and EMG activity were recorded. The T10MWs were recorded under three conditions: standard (wearing shoes), reduced grip (wearing socks) and increased cognitive load (backward-counting dual-task). PwPMS showed worse kinematics of gait and increased muscle coactivation than controls at both the thigh and leg levels. Both reduced grip and increased cognitive load caused a reduction in the cadence and velocity of the T10MW, which were correlated with one another. A higher coactivation index at the thigh level of the more affected side was positively correlated with the time of the T10MW (r = 0.5, p < 0.01), Expanded Disability Status Scale (EDSS) (r = 0.4, p < 0.05), and negatively correlated with the cadence (r = −0.6, p < 0.001). Our results suggest that excessive coactivation at the thigh level is the major determinant of the gait performance as the disease progresses. Moreover, demanding walking conditions do not influence gait in controls but deteriorate walking performances in PwPMS, thus those conditions should be prevented during hospital examinations as well as in homecare environments

Intensive Neurorehabilitation and Gait Improvement in Progressive Multiple Sclerosis: Clinical, Kinematic and Electromyographic Analysis

Background: Gait deficit is a hallmark of multiple sclerosis and the walking capacity can be improved with neurorehabilitation. Technological advances in biomechanics offer opportunities to assess the effects of rehabilitation objectively. Objective: Combining wireless surface electromyography and wearable inertial sensors to assess and monitor the gait pattern before and after an intensive multidisciplinary neurorehabilitation program (44 h/4weeks) to evaluate rehabilitation efficiency. Methods: Forty people with progressive multiple sclerosis were enrolled. Wireless wearable devices were used to evaluate the gait. Instrumental gait analysis, clinical assessment, and patient report outcome measures were acquired before and after the neurorehabilitation. Spatiotemporal gait parameters, the co-activation index of lower limb muscles, and clinical assessments were compared pre- and post-treatment. Results: Significant improvements after intensive neurorehabilitation were found in most of the clinical assessments, cadence, and velocity of the instrumental gait analysis, paralleled by amelioration of thigh co-activation on the less-affected side. Subjects with better balance performance and higher independence at baseline benefit more from the neurorehabilitation course. Conclusions: Significant improvements in gait performance were found in our cohort after an intensive neurorehabilitation course, for both quantitative and qualitative measures. Integrating kinematic and muscle activity measurements offers opportunities to objectively evaluate and interpret treatment effects

Data from: Prognostic value of serum neurofilaments in patients with clinically isolated syndromes

Objectives: To assess the prognostic role of serum neurofilament light chains (Nfls) for Clinically Defined Multiple Sclerosis (CDMS) and McDonald 2017 MS in patients with Clinically Isolated Syndromes (CIS). Methods: we retrospectively analyzed data of patients admitted at our neurological department between 2000 to 2015 for a first demyelinating event. We evaluated baseline serum Nfls in addition to CSF, MRI, and clinical data. Results: Amongst 222 patients who were enrolled (mean follow-up 100.6 months), 45 patients (20%) developed CDMS and 141 patients (63.5%) developed 2017 MS at two years. Serum Nfls (median 22.0, IQR 11.6-40.4 pg/ml) were noticeably increased in patients who have suffered a recent relapse, with a high number of T2 and Gd enhancing lesions at baseline MRI. Serum Nfls were prognostic for both CDMS and McDonald 2017 MS, with a three-fold and a two-fold respective reduction in CDMS and 2017 MS risk in those patients with low and extremely low levels of Nfl. The results remained unchanged subsequent to adjustment for such established MS prognostic factors as oligoclonal bands’ presence, Gd-enhancing lesion, and a high T2 lesion load at baseline MRI. Nfls were associated with baseline disability but not at follow-up. Conclusions: Serum Nfls have a prognostic value for CIS patient conversion to MS. Nfls might play a twin role as biomarkers in MS as peak level measurements can act as a quantitative marker of serious inflammatory activity, while steady-state levels can be a reflection of neurodegenerative and chronic inflammatory processes