Towards remote monitoring of Parkinson’s disease tremor using wearable motion capture systems

Delrobaei, Mehdi; Memar, Sara; Pieterman, Marcus; Stratton, Tyler W.; McIsaac, Kenneth; Jog, Mandar

doi:10.1016/j.jns.2017.11.004

Cited by 84 publications

(79 citation statements)

References 39 publications

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“…The somatosensory systems might still be activated by the neural activity and thus produce sensations of motion or distortions manifested as shaking or vibration in the body [26]. Prior reports suggest that the internal tremor sensations [26] could be caused by a physical movement from subclinical muscle activity producing a tremor that cannot be observed visually [27,28] but can be detected with advanced technical recording methods [6][7][8].…”

Section: Discussionmentioning

confidence: 99%

“…The neuronal activity from basal ganglia structures and the thalamus shows rhythmic activity related to tremor [4], suggesting that Parkinsonian tremor arises from central oscillators [5]. To gain further insights into tremor generation and presentation, noninvasive techniques -such as motion capturehave been employed [6][7][8]. The development of advanced recording systems and signal processing algorithms over the last few decades has provided methods that are more sensitive at detecting tremor.…”

Section: Introductionmentioning

confidence: 99%

“…Some key advantages of technical recording methods are their ability to objectively and repeatedly provide precise and detailed information about the characteristics of tremor (e.g., peak amplitude, frequency) compared to subjective visual inspection. For example, the higher accuracy and precision of modern motion capture systems may be utilized in research and in clinical settings to evaluate and customize treatment of tremor [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

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Exploring the effects of deep brain stimulation and vision on tremor in Parkinson’s disease - benefits from objective methods

Fransson

Nilsson

Nyström

et al. 2020

J NeuroEngineering Rehabil

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Background: Tremor is a cardinal symptom of Parkinson's disease (PD) that may cause severe disability. As such, objective methods to determine the exact characteristics of the tremor may improve the evaluation of therapy. This methodology study aims to validate the utility of two objective technical methods of recording Parkinsonian tremor and evaluate their ability to determine the effects of Deep Brain Stimulation (DBS) of the subthalamic nucleus and of vision. Methods: We studied 10 patients with idiopathic PD, who were responsive to L-Dopa and had more than 1 year use of bilateral subthalamic nucleus stimulation. The patients did not have to display visible tremor to be included in the study. Tremor was recorded with two objective methods, a force platform and a 3 dimensional (3D) motion capture system that tracked movements in four key proximal sections of the body (knee, hip, shoulder and head). They were assessed after an overnight withdrawal of anti-PD medications with DBS ON and OFF and with eyes open and closed during unperturbed and perturbed stance with randomized calf vibration, using a randomized test order design. Results: Tremor was detected with the Unified Parkinson's Disease Rating Scale (UPDRS) in 6 of 10 patients but only distally (hands and feet) with DBS OFF. With the force platform and the 3D motion capture system, tremor was detected in 6 of 10 and 7 of 10 patients respectively, mostly in DBS OFF but also with DBS ON in some patients. The 3D motion capture system revealed that more than one body section was usually affected by tremor and that the tremor amplitude was non-uniform, but the frequency almost identical, across sites. DBS reduced tremor amplitude non-uniformly across the body. Visual input mostly reduced tremor amplitude with DBS ON. Conclusions: Technical recording methods offer objective and sensitive detection of tremor that provide detailed characteristics such as peak amplitude, frequency and distribution pattern, and thus, provide information that can guide the optimization of treatments. Both methods detected the effects of DBS and visual input but the 3D motion system was more versatile in that it could detail the presence and properties of tremor at individual body sections.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Exploring the effects of deep brain stimulation and vision on tremor in Parkinson’s disease - benefits from objective methods

Fransson

Nilsson

Nyström

et al. 2020

J NeuroEngineering Rehabil

View full text Add to dashboard Cite

show abstract

“…Good reliability results regarding optical motion capture have been described for the assessment of cervical and thoracolumbar range of motion (ROM) [21,22]. Their use in neurological diseases includes balance assessments in multiple sclerosis [23,24], Parkinsonian tremor [25,26], or range of motion (ROM) in stroke [27]. Nevertheless, further studies are necessary to confirm the clinical and predictive importance of measurements with IMUs [13,23].…”

Section: Introductionmentioning

confidence: 99%

Concurrent Validity and Reliability of an Inertial Measurement Unit for the Assessment of Craniocervical Range of Motion in Subjects with Cerebral Palsy

et al. 2020

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Objective: This study aimed to determine the validity and reliability of Inertial Measurement Units (IMUs) for the assessment of craniocervical range of motion (ROM) in patients with cerebral palsy (CP). Methods: twenty-three subjects with CP and 23 controls, aged between 4 and 14 years, were evaluated on two occasions, separated by 3 to 5 days. An IMU and a Cervical Range of Motion device (CROM) were used to assess craniocervical ROM in the three spatial planes. Validity was assessed by comparing IMU and CROM data using the Pearson correlation coefficient, the paired t-test and Bland–Altman plots. Intra-day and inter-day relative reliability were determined using the Intraclass Correlation Coefficient (ICC). The Standard Error of Measurement (SEM) and the Minimum Detectable Change at a 90% confidence level (MDC90) were obtained for absolute reliability. Results: High correlations were detected between methods in both groups on the sagittal and frontal planes (r > 0.9), although this was reduced in the case of the transverse plane. Bland–Altman plots indicated bias below 5º, although for the range of cervical rotation in the CP group, this was 8.2º. The distance between the limits of agreement was over 23.5º in both groups, except for the range of flexion-extension in the control group. ICCs were higher than 0.8 for both comparisons and groups, except for inter-day comparisons of rotational range in the CP group. Absolute reliability showed high variability, with most SEM below 8.5º, although with worse inter-day results, mainly in CP subjects, with the MDC90 of rotational range achieving more than 20º. Conclusions: IMU application is highly correlated with CROM for the assessment of craniocervical movement in CP and healthy subjects; however, both methods are not interchangeable. The IMU error of measurement can be considered clinically acceptable; however, caution should be taken when this is used as a reference measure for interventions.

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“…Monitoring PD symptoms through wearable sensors, or "wearables," containing accelerometers and/or gyroscopes has gained considerable interest, and important progress has been made in the last decade. 56 Wearables are successful in predicting and detecting tremor 46,48,57 and show promise in assessing freezing of gait, 58 bradykinesia, and dyskinesia. [59][60][61] Numerous studies based on tremor detection have supported the feasibility, effectiveness, and efficiency of wearables-based aDBS.…”

Section: Adbs Based On Wearable Sensorsmentioning

confidence: 99%

An update on adaptive deep brain stimulation in Parkinson's disease

et al. 2018

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Advancing conventional open‐loop DBS as a therapy for PD is crucial for overcoming important issues such as the delicate balance between beneficial and adverse effects and limited battery longevity that are currently associated with treatment. Closed‐loop or adaptive DBS aims to overcome these limitations by real‐time adjustment of stimulation parameters based on continuous feedback input signals that are representative of the patient's clinical state. The focus of this update is to discuss the most recent developments regarding potential input signals and possible stimulation parameter modulation for adaptive DBS in PD. Potential input signals for adaptive DBS include basal ganglia local field potentials, cortical recordings (electrocorticography), wearable sensors, and eHealth and mHealth devices. Furthermore, adaptive DBS can be applied with different approaches of stimulation parameter modulation, the feasibility of which can be adapted depending on specific PD phenotypes. Implementation of technological developments like machine learning show potential in the design of such approaches; however, energy consumption deserves further attention. Furthermore, we discuss future considerations regarding the clinical implementation of adaptive DBS in PD. © 2018 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

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Towards remote monitoring of Parkinson’s disease tremor using wearable motion capture systems

Cited by 84 publications

References 39 publications

Exploring the effects of deep brain stimulation and vision on tremor in Parkinson’s disease - benefits from objective methods

Exploring the effects of deep brain stimulation and vision on tremor in Parkinson’s disease - benefits from objective methods

Concurrent Validity and Reliability of an Inertial Measurement Unit for the Assessment of Craniocervical Range of Motion in Subjects with Cerebral Palsy

An update on adaptive deep brain stimulation in Parkinson's disease

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