Automatic real-time monitoring and assessment of tremor parameters in the upper limb from orientation data

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.

Peripherical Electrical Stimulation for Parkinsonian Tremor: A Systematic Review

Parkinsonian tremor is one of the most common motor disorders in patients with Parkinson's disease (PD). Compared to oral medications and brain surgery, electrical stimulation approaches have emerged as effective and non-invasive methods for tremor reduction. The pathophysiology, detection and interventions of tremors have been introduced, however, a systematic review of peripherical electrical stimulation approaches, methodologies, experimental design and clinical outcomes for PD tremor suppression is still missing. Therefore, in this paper, we summarized recent studies on electrical stimulation for tremor suppression in PD patients and discussed stimulation protocols and effectiveness of different types of electrical stimulation approaches in detail. Twenty out of 528 papers published from 2010 to 2021 July were reviewed. The results show that electrical stimulation is an efficient intervention for tremor suppression. The methods fall into three main categories according to the mechanisms: namely functional electrical stimulation (FES), sensory electrical stimulation (SES) and transcutaneous electrical nerve stimulation (TENS). The outcomes of tremor suppression were varied due to various stimulation approaches, electrode locations and stimulation parameters. The FES method performed the best in tremor attenuation where the efficiency depends mainly by the control strategy and accuracy of tremor detection. However, the mechanism underlying tremor suppression with SES and TENS, is not well-known. Current electrical stimulation approaches may only work for a number of patients. The potential mechanism of tremor suppression still needs to be further explored.

Wearable Peripheral Electrical Stimulation Devices for the Reduction of Essential Tremor: A Review

Essential tremor is the most common pathological tremor, with a prevalence of 6.3% in people over 65 years of age. This disorder interferes with a patient's ability to carry out activities of daily living independently, and treatment with medical and surgical interventions is often insufficient or contraindicated. Mechanical orthoses have not been widely adopted by patients due to discomfort and lack of discretion. Over the past 30 years, peripheral electrical stimulation has been investigated as a possible treatment for patients who have not found other treatment options to be satisfactory, with wearable devices revolutionizing this emerging approach in recent years. In this paper, an overview of essential tremor and its current medical and surgical treatment options are presented. Following this, tremor detection, measurement and characterization methods are explored with a focus on the measurement options that can be incorporated into wearable devices. Then, novel interventions for essential tremor are described, with a detailed review of open and closed-loop peripheral electrical stimulation methods. Finally, discussion of the need for wearable closed-loop peripheral electrical stimulation devices for essential tremor, approaches in their implementation, and gaps in the literature for further research are presented.

Characterization of Parkinsonian Hand Tremor and Validation of a High-Order Tremor Estimator

Recent progress in wearable technology has made wearable tremor suppression devices (WTSDs) for Parkinson's patients a potentially viable alternative solution for tremor management. So far, in contrast to wrist and elbow tremor, finger tremors have not been studied in depth despite the huge impact that they have on a patient's daily life. In addition, more evidence has been found showing that the performance of current tremor estimators may be limited by their model order due to the multiple harmonics present in tremor. The aim of this paper is to characterize finger and wrist tremor in both the time and frequency domains, and to propose a high-order tremor estimation algorithm. Tremor magnitudes are reported in the forms of linear acceleration, angular velocity, and angular displacement. The activation of forearm flexor and extensor muscles is also investigated. The frequency analysis shows that Parkinsonian tremors produce oscillations of the hand with pronounced harmonics. At last, a high-order weighted-frequency Fourier linear combiner (WFLC)-based Kalman filter is proposed. The percentage estimation accuracy achieved from the proposed estimator is 96.3 ± 1.7%, showing average improvements of 28.5% and 48.9% over its lower-order counterpart and the WFLC. The proposed estimator shows promise for use in a WTSD.

Essential tremor quantification based on the combined use of a smartphone and a smartwatch: The NetMD study

BACKGROUND

The use of wearable technology is an emerging field of research in movement disorders. This paper introduces a clinical study to evaluate the feasibility, clinical correlation and reliability of using a system based in smartwatches to quantify tremor in essential tremor (ET) patients and check its acceptance as clinical monitoring tool.

NEW METHOD

The system is based on a commercial smartwatch and an Android smartphone. An investigational Android application controls the process of recording raw data from the smartwatch three-dimensional gyroscopes. Thirty-four ET patients were consecutively enrolled in the experiments and assessed along one year. Arm tremor was videofilmed and scored using the Fahn-Tolosa-Marin Tremor Rating Scale (FTM-TRS). Tremor intensity was quantified with the root mean square of angular velocity measured in the patients' wrists.

RESULTS

Eighty-two assessments with smartwatches were performed. Spearman's correlation coefficients (ρ) between clinical tremor (FTM-TRS) scores and smartwatch measures for tremor intensity were 0.590 at rest; ρ = 0.738 in steady posture; ρ = 0.189 in finger-to-nose maneuvers; and ρ = 0.652 in pouring water task. Smartwatch reliability was checked by intraclass realiability coefficients: 0.85, 0.95, 0.91, 0.95 respectively. Most of patients showed good acceptance of the system.

COMPARISON WITH EXISTING METHOD(S)

This commodity hardware contributes to quantify tremor objectively in a consulting-room by customized Android smart devices as clinical monitoring tool.

CONCLUSIONS

The NetMD system for tremor analysis is feasible, well-correlated with clinical scores, reliable and well-accepted by patients to tremor follow-up. Therefore, it could be an option to objectively quantify tremor in ET patients during their regular follow-up.

An In-Laboratory Validity and Reliability Tested System for Quantifying Hand-Arm Tremor in Motions

Despite the advancement of the tremor assessment systems, the current technology still lacks a method that can objectively characterize tremors in relative segmental movements. This paper presents a measurement system, which quantifies multi-degrees-of-freedom coupled relative motions of hand-arm tremor, in terms of joint angular displacement. In-laboratory validity and reliability tests of the system algorithm to provide joint angular displacement was carried out by using the two-degrees-of-freedom tremor simulator with incremental rotary encoder systems installed. The statistical analyses show that the developed system has high validity results and comparable reliability performances using the rotary encoder system as the reference. In the clinical trials, the system was tested on 38 Parkinson's disease patients. The system readings were correlated with the observational tremor ratings of six trained medical doctors. The moderate to very high clinical correlations of the system readings in measuring rest, postural and task-specific tremors add merits to the degree of readiness of the developed tremor measurement system in a routine clinical setting and/or intervention trial for tremor amelioration.

Transducer-based evaluation of tremor

The International Parkinson and Movement Disorder Society established a task force on tremor that reviewed the use of transducer-based measures in the quantification and characterization of tremor. Studies of accelerometry, electromyography, activity monitoring, gyroscopy, digitizing tablet-based measures, vocal acoustic analysis, and several other transducer-based methods were identified by searching PubMed.gov. The availability, use, acceptability, reliability, validity, and responsiveness were reviewed for each measure using the following criteria: (1) used in the assessment of tremor; (2) used in published studies by people other than the developers; and (3) adequate clinimetric testing. Accelerometry, gyroscopy, electromyography, and digitizing tablet-based measures fulfilled all three criteria. Compared to rating scales, transducers are far more sensitive to changes in tremor amplitude and frequency, but they do not appear to be more capable of detecting a change that exceeds random variability in tremor amplitude (minimum detectable change). The use of transducer-based measures requires careful attention to their limitations and validity in a particular clinical or research setting. © 2016 International Parkinson and Movement Disorder Society.

Using Portable Transducers to Measure Tremor Severity

BACKGROUND

Portable motion transducers, suitable for measuring tremor, are now available at a reasonable cost. The use of these transducers requires knowledge of their limitations and data analysis. The purpose of this review is to provide a practical overview and example software for using portable motion transducers in the quantification of tremor.

METHODS

Medline was searched via PubMed.gov in December 2015 using the Boolean expression "tremor AND (accelerometer OR accelerometry OR gyroscope OR inertial measurement unit OR digitizing tablet OR transducer)." Abstracts of 419 papers dating back to 1964 were reviewed for relevant portable transducers and methods of tremor analysis, and 105 papers written in English were reviewed in detail.

RESULTS

Accelerometers, gyroscopes, and digitizing tablets are used most commonly, but few are sold for the purpose of measuring tremor. Consequently, most software for tremor analysis is developed by the user. Wearable transducers are capable of recording tremor continuously, in the absence of a clinician. Tremor amplitude, frequency, and occurrence (percentage of time with tremor) can be computed. Tremor amplitude and occurrence correlate strongly with clinical ratings of tremor severity.

DISCUSSION

Transducers provide measurements of tremor amplitude that are objective, precise, and valid, but the precision and accuracy of transducers are mitigated by natural variability in tremor amplitude. This variability is so great that the minimum detectable change in amplitude, exceeding random variability, is comparable for scales and transducers. Research is needed to determine the feasibility of detecting smaller change using averaged data from continuous long-term recordings with wearable transducers.

Prediction of the Wrist Joint Position During a Postural Tremor Using Neural Oscillators and an Adaptive Controller

The prediction of the joint angle position, especially during tremor bursts, can be useful for detecting, tracking, and forecasting tremors. Thus, this research proposes a new model for predicting the wrist joint position during rhythmic bursts and inter-burst intervals. Since a tremor is an approximately rhythmic and roughly sinusoidal movement, neural oscillators have been selected to underlie the proposed model. Two neural oscillators were adopted. Electromyogram (EMG) signals were recorded from the extensor carpi radialis and flexor carpi radialis muscles concurrent with the joint angle signals of a stroke subject in an arm constant-posture. The output frequency of each oscillator was equal to the frequency corresponding to the maximum value of power spectrum related to the rhythmic wrist joint angle signals which had been recorded during a postural tremor. The phase shift between the outputs of the two oscillators was equal to the phase shift between the muscle activation of the wrist flexor and extensor muscles. The difference between the two oscillators' output signals was considered the main pattern. Along with a proportional compensator, an adaptive neural controller has adjusted the amplitude of the main pattern in such a way so as to minimize the wrist joint prediction error during a stroke patient's tremor burst and a healthy subject's generated artificial tremor. In regard to the range of wrist joint movement during the observed rhythmic motions, a calculated prediction error is deemed acceptable.