Hilbert-Huang transform based instrumental assessment of intention tremor in multiple sclerosis

Upper limb intention tremor assessment: opportunities and challenges in wearable technology

BACKGROUND

Tremors are involuntary rhythmic movements commonly present in neurological diseases such as Parkinson's disease, essential tremor, and multiple sclerosis. Intention tremor is a subtype associated with lesions in the cerebellum and its connected pathways, and it is a common symptom in diseases associated with cerebellar pathology. While clinicians traditionally use tests to identify tremor type and severity, recent advancements in wearable technology have provided quantifiable ways to measure movement and tremor using motion capture systems, app-based tasks and tools, and physiology-based measurements. However, quantifying intention tremor remains challenging due to its changing nature.

METHODOLOGY & RESULTS

This review examines the current state of upper limb tremor assessment technology and discusses potential directions to further develop new and existing algorithms and sensors to better quantify tremor, specifically intention tremor. A comprehensive search using PubMed and Scopus was performed using keywords related to technologies for tremor assessment. Afterward, screened results were filtered for relevance and eligibility and further classified into technology type. A total of 243 publications were selected for this review and classified according to their type: body function level: movement-based, activity level: task and tool-based, and physiology-based. Furthermore, each publication's methods, purpose, and technology are summarized in the appendix table.

CONCLUSIONS

Our survey suggests a need for more targeted tasks to evaluate intention tremors, including digitized tasks related to intentional movements, neurological and physiological measurements targeting the cerebellum and its pathways, and signal processing techniques that differentiate voluntary from involuntary movement in motion capture systems.

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.

Assessment of movement disorders using wearable sensors during upper limb tasks: A scoping review

Background: Studies aiming to objectively quantify movement disorders during upper limb tasks using wearable sensors have recently increased, but there is a wide variety in described measurement and analyzing methods, hampering standardization of methods in research and clinics. Therefore, the primary objective of this review was to provide an overview of sensor set-up and type, included tasks, sensor features and methods used to quantify movement disorders during upper limb tasks in multiple pathological populations. The secondary objective was to identify the most sensitive sensor features for the detection and quantification of movement disorders on the one hand and to describe the clinical application of the proposed methods on the other hand. Methods: A literature search using Scopus, Web of Science, and PubMed was performed. Articles needed to meet following criteria: 1) participants were adults/children with a neurological disease, 2) (at least) one sensor was placed on the upper limb for evaluation of movement disorders during upper limb tasks, 3) comparisons between: groups with/without movement disorders, sensor features before/after intervention, or sensor features with a clinical scale for assessment of the movement disorder. 4) Outcome measures included sensor features from acceleration/angular velocity signals. Results: A total of 101 articles were included, of which 56 researched Parkinson's Disease. Wrist(s), hand(s) and index finger(s) were the most popular sensor locations. Most frequent tasks were: finger tapping, wrist pro/supination, keeping the arms extended in front of the body and finger-to-nose. Most frequently calculated sensor features were mean, standard deviation, root-mean-square, ranges, skewness, kurtosis/entropy of acceleration and/or angular velocity, in combination with dominant frequencies/power of acceleration signals. Examples of clinical applications were automatization of a clinical scale or discrimination between a patient/control group or different patient groups. Conclusion: Current overview can support clinicians and researchers in selecting the most sensitive pathology-dependent sensor features and methodologies for detection and quantification of upper limb movement disorders and objective evaluations of treatment effects. Insights from Parkinson's Disease studies can accelerate the development of wearable sensors protocols in the remaining pathologies, provided that there is sufficient attention for the standardisation of protocols, tasks, feasibility and data analysis methods.

Tremor in Multiple Sclerosis-An Overview and Future Perspectives

Tremor is an important and common symptom in patients with multiple sclerosis (MS). It constituted one of the three core features of MS triad described by Charcot in the last century. Tremor could have a drastic impact on patients' quality of life. This paper provides an overview of tremor in MS and future perspectives with a particular emphasis on its epidemiology (prevalence: 25-58%), clinical characteristics (i.e., large amplitude 2.5-7 Hz predominantly postural or intention tremor vs. exaggerated physiological tremor vs. pseudo-rhythmic activity arising from cerebellar dysfunction vs. psychogenic tremor), pathophysiological mechanisms (potential implication of cerebellum, cerebello-thalamo-cortical pathways, basal ganglia, and brainstem), assessment modalities (e.g., tremor rating scales, Stewart-Holmes maneuver, visual tracking, digitized spirography and accelerometric techniques, accelerometry-electromyography coupling), and therapeutic options (i.e., including pharmacological agents, botulinum toxin A injections; deep brain stimulation or thalamotomy reserved for severe, disabling, or pharmaco-resistant tremors). Some suggestions are provided to help overcome the unmet needs and guide future therapeutic and diagnostic studies in this complex disorder.

Beyond center-based testing: Understanding and improving functioning with wearable technology in MS

Wearable sensors are designed to be worn on the body or embedded into portable devices (e.g. smartphones and smartwatches), allowing continuous patient-based monitoring, objective outcomes measuring, and feedback delivering on daily-life activities. Within the medicine domain, there has been a rapid increase in the development, testing, and use of wearable technologies especially in the context of neurological diseases. Although wearables represent promising tools also in multiple sclerosis (MS), the research on their application in MS is still ongoing, and further studies are required to assess their reliability and accuracy to monitor body functions and disability in people with MS (pwMS). Here, we provided a comprehensive overview of the opportunities, potential challenges, and limitations of the wearable technology use in MS. In particular, we classified previous findings within this field into macro-categories, considered crucial for disease management: assessment, monitoring, intervention, advice, and education. Given the increasing pivotal role played by wearables, current literature suggests that for pwMS, the time is right to shift from a center-based traditional therapeutic paradigm toward a personalized patient-based disease self-management. On this way, we present two ongoing initiatives aimed at implementing a continuous monitoring of pwMS and, consequently, providing timely and appropriate care interventions.

Biosensors to monitor MS activity

Advances in wearable and wireless biosensing technology pave the way for a brave new world of novel multiple sclerosis (MS) outcome measures. Our current tools for examining patients date back to the 19th century and while invaluable to the neurologist invite accompaniment from these new technologies and artificial intelligence (AI) analytical methods. While the most common biosensor tool used in MS publications to date is the accelerometer, the landscape is changing quickly with multi-sensor applications, electrodermal sensors, and wireless radiofrequency waves. Some caution is warranted to ensure novel outcomes have clear clinical relevance and stand-up to the rigors of reliability, reproducibility, and precision, but the ultimate implementation of biosensing in the MS clinical setting is inevitable.

A Survey of Assistive Technologies for Assessment and Rehabilitation of Motor Impairments in Multiple Sclerosis

Multiple sclerosis (MS) is a disease that affects the central nervous system, which consists of the brain and spinal cord. Although this condition cannot be cured, proper treatment of persons with MS (PwMS) can help control and manage the relapses of several symptoms. In this survey article, we focus on the different technologies used for the assessment and rehabilitation of motor impairments for PwMS. We discuss sensor-based and robot-based solutions for monitoring, assessment and rehabilitation. Among MS symptoms, fatigue is one of the most disabling features, since PwMS may need to put significantly more intense effort toward achieving simple everyday tasks. While fatigue is a common symptom across several neurological chronic diseases, it remains poorly understood for various reasons, including subjectivity and variability among individuals. To this end, we also investigate recent methods for fatigue detection and monitoring. The result of this survey will provide both clinicians and researchers with valuable information on assessment and rehabilitation technologies for PwMS, as well as providing insights regarding fatigue and its effect on performance in daily activities for PwMS.

Biosensing in multiple sclerosis

INTRODUCTION

The goal of using wearable biosensors in multiple sclerosis (MS) is to provide outcome metrics with higher sensitivity to deficits and better inter-test and inter-rater reliability than standard neurological exam bedside maneuvers. A wearable biosensor not only has the potential to enhance physical exams, but also offers the promise of remote evaluations of the patient either at home or with local non-specialist providers. Areas covered: We performed a structured literature review on the use of wearable biosensors in studies of multiple sclerosis. This included accelerometers, gyroscopes, eye-trackers, grip sensors, and multi-sensors. Expert commentary: Wearable sensors that are sensitive to change in function over time have great potential to serve as outcome metrics in clinical trials. Key features of generalizability are simplicity in the application of the device and delivery of data to the provider. Another important feature to establish is best sampling rate. Having too high of a sampling rate can lead to over-interpretation of noisy data On the other hand, a low sampling rate can result in an insensitive test thus missing subtle changes of clinical interest. Of most importance is to establish metrics derived from wearable devices that provide meaningful data in longitudinal studies.