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MHealth and wearable technology should replace motor diaries to track motor fluctuations in Parkinson's disease.

ABSTRACT: Accurately monitoring motor and non-motor symptoms as well as complications in people with Parkinson's disease (PD) is a major challenge, both during clinical management and when conducting clinical trials investigating new treatments. A variety of strategies have been relied upon including questionnaires, motor diaries, and the serial administration of structured clinical exams like part III of the MDS-UPDRS. To evaluate the potential use of mobile and wearable technologies in clinical trials of new pharmacotherapies targeting PD symptoms, we carried out a project (project BlueSky) encompassing four clinical studies, in which 60 healthy volunteers (aged 23-69; 33 females) and 95 people with PD (aged 42-80; 37 females; years since diagnosis 1-24 years; Hoehn and Yahr 1-3) participated and were monitored in either a laboratory environment, a simulated apartment, or at home and in the community. In this paper, we investigated (i) the utility and reliability of self-reports for describing motor fluctuations; (ii) the agreement between participants and clinical raters on the presence of motor complications; (iii) the ability of video raters to accurately assess motor symptoms, and (iv) the dynamics of tremor, dyskinesia, and bradykinesia as they evolve over the medication cycle. Future papers will explore methods for estimating symptom severity based on sensor data. We found that 38% of participants who were asked to complete an electronic motor diary at home missed ~25% of total possible entries and otherwise made entries with an average delay of >4?h. During clinical evaluations by PD specialists, self-reports of dyskinesia were marked by ~35% false negatives and 15% false positives. Compared with live evaluation, the video evaluation of part III of the MDS-UPDRS significantly underestimated the subtle features of tremor and extremity bradykinesia, suggesting that these aspects of the disease may be underappreciated during remote assessments. On the other hand, live and video raters agreed on aspects of postural instability and gait. Our results highlight the significant opportunity for objective, high-resolution, continuous monitoring afforded by wearable technology to improve upon the monitoring of PD symptoms.

SUBMITTER: Erb MK

PROVIDER: S-EPMC6969057 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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mHealth and wearable technology should replace motor diaries to track motor fluctuations in Parkinson's disease.

Erb M Kelley MK Karlin Daniel R DR Ho Bryan K BK Thomas Kevin C KC Parisi Federico F Vergara-Diaz Gloria P GP Daneault Jean-Francois JF Wacnik Paul W PW Zhang Hao H Kangarloo Tairmae T Demanuele Charmaine C Brooks Chris R CR Detheridge Craig N CN Shaafi Kabiri Nina N Bhangu Jaspreet S JS Bonato Paolo P

NPJ digital medicine 20200117

Accurately monitoring motor and non-motor symptoms as well as complications in people with Parkinson's disease (PD) is a major challenge, both during clinical management and when conducting clinical trials investigating new treatments. A variety of strategies have been relied upon including questionnaires, motor diaries, and the serial administration of structured clinical exams like part III of the MDS-UPDRS. To evaluate the potential use of mobile and wearable technologies in clinical trials o ...[more]

PMID: 31970291

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Project description:ObjectiveIdentifying neural activity biomarkers of brain disease is essential to provide objective estimates of disease burden, obtain reliable feedback regarding therapeutic efficacy, and potentially to serve as a source of control for closed-loop neuromodulation. In Parkinson's disease (PD), microelectrode recordings (MER) are routinely performed in the basal ganglia to guide electrode implantation for deep brain stimulation (DBS). While pathologically-excessive oscillatory activity has been observed and linked to PD motor dysfunction broadly, the extent to which these signals provide quantitative information about disease expression and fluctuations, particularly at short timescales, is unknown. Furthermore, the degree to which informative signal features are similar or different across patients has not been rigorously investigated. We sought to determine the extent to which motor error in PD across patients can be decoded on a rapid timescale using spectral features of neural activity.ApproachHere, we recorded neural activity from the subthalamic nucleus (STN) of subjects with PD undergoing awake DBS surgery while they performed an objective, continuous behavioral assessment that synthesized heterogenous PD motor manifestations to generate a scalar measure of motor dysfunction at short timescales. We then leveraged natural motor performance variations as a 'ground truth' to identify corresponding neurophysiological biomarkers.Main resultsSupport vector machines using multi-spectral decoding of neural signals from the STN succeeded in tracking the degree of motor impairment at short timescales (as short as one second). Spectral power across a wide range of frequencies, beyond the classic 'β' oscillations, contributed to this decoding, and multi-spectral models consistently outperformed those generated using more isolated frequency bands. While generalized decoding models derived across subjects were able to estimate motor impairment, patient-specific models typically performed better.SignificanceThese results demonstrate that quantitative information about short-timescale PD motor dysfunction is available in STN neural activity, distributed across various patient-specific spectral components, such that an individualized approach will be critical to fully harness this information for optimal disease tracking and closed-loop neuromodulation.

Project description:Background: Parkinson's disease (PD) is a neurodegenerative disease in which the progressive loss of dopaminergic neurons (DA) leads to initially sporadic and eventually widespread damage of the nervous system resulting in significant musculoskeletal and cognitive deterioration. Loss of motor function alongside increasing cognitive impairment is part of the natural disease progression. Gait is often considered an automatic activity; however, walking is the result of a delicate balance of multiple systems which maintain the body's center of mass over an ever-changing base of support. It is a complex motor behavior that requires components of attention and memory to prevent falls and injury. In addition, evidence points to the critical role of salient visual information to gait adaptability. There is a growing understanding that treatment for PD needs to address movement as it occurs naturally and walking needs to be practiced in more complex environments than traditional therapy has provided.MethodsIn this single-blinded randomized-controlled pilot study, an immersive treadmill training was piloted to determine feasibility and preliminary efficacy on gait and cognition in people with PD. Eighteen participants with Hoehn and Yahr stages I-III PD were randomized to either an intervention or a waitlist control group. Following baseline data collection, the intervention group trained for 30 min, three times/week for 4 weeks on a split belt treadmill combined with a first-person immersive video game targeting visuospatial skills and working memory. Assessment was repeated after 4 weeks of training for the experimental group and 1-month after baseline for the control group. Primary motor outcomes were captured with the APDM Opal sensors during 6 MWT, TUG, and TUG Cognitive. Secondary outcomes of cognition were measured with the Montreal Cognitive Assessment (MoCA), Verbal Fluency (Fruit, Vegetable, and Animal) and the Symbol Digit Modality Test (SDMT). Within subject differences were calculated using the Wilcoxon Signed Ranked Test and between subject comparisons were analyzed using the Mann Whitney U-test.ResultsThis novel treadmill training program was well-tolerated with all participants in the intervention group completing 4 weeks of training three times a week without any adverse effects. After immersive cognitive motor training, the experimental group made clinically relevant improvements in gait speed and walking distance during the 6 MWT while members of the control group showed no change or decreased gait speed and walking distance over the 1-month trial. In addition, the experimental group demonstrated significant improvement for the TUG Cognitive (p = 0.05) and those changes were greater than the control group (between group p = 0.040). The experimental group also improved scores on MoCA (p = 0.007) and SDMT (p = 0.01) cognitive outcome measures while the control group did not.ConclusionThe use of immersive gaming technology to engage specific areas of cognition related to gait is feasible in PD. The treadmill training program paired with a customized interactive video game improved walking velocity in addition to non-significant but consistent improvements in other gait measures and cognitive performance in participants with early to mid-stage PD.

Project description:BackgroundBalance impairments, that lead to falls, are one of the main symptoms of Parkinson's disease (PD). Telerehabilitation is becoming more common for people with PD; however, balance is particularly challenging to assess and treat virtually. The feasibility and efficacy of virtual assessment and virtual treatment of balance in people with PD are unknown. The present study protocol has three aims: I) to determine if a virtual balance and gait assessment (instrumented L-shape mobility test) with wearable sensors can predict a gold-standard, in-person clinical assessment of balance, the Mini Balance Evaluation Systems Test (Mini-BESTest); II) to explore the effects of 12 sessions of balance telerehabilitation and unsupervised home exercises on balance, gait, executive function, and clinical scales; and III) to explore if improvements after balance telerehabilitation transfer to daily-life mobility, as measured by instrumented socks with inertial sensors worn for 7 days.MethodsThe TelePD Trial is a prospective, single-center, parallel-group, single-blind, pilot, randomized, controlled trial. This trial will enroll 80 eligible people with PD. Participants will be randomized at a 1:1 ratio into receiving home-based balance exercises in either: 1) balance telerehabilitation (experimental group, n = 40) or 2) unsupervised exercises (control group, n = 40). Both groups will perform 12 sessions of exercise at home that are 60 min long. The primary outcome will be Mini-BESTest. The secondary outcomes will be upper and lower body gait metrics from a prescribed task (instrumented L-shape mobility test); daily-life mobility measures over 7 days with wearable sensors in socks, instrumented executive function tests, and clinical scales. Baseline testing and 7 days of daily-life mobility measurement will occur before and after the intervention period.ConclusionThe TelePD Trial will be the first to explore the usefulness of using wearable sensor-based measures of balance and gait remotely to assess balance, the feasibility and efficacy of balance telerehabilitation in people with PD, and the translation of balance improvements after telerehabilitation to daily-life mobility. These results will help to develop a more effective home-based balance telerehabilitation and virtual assessment that can be used remotely in people with balance impairments.Trial registrationThis trial was prospectively registered on ClinicalTrials.gov (NCT05680597).

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MHealth and wearable technology should replace motor diaries to track motor fluctuations in Parkinson's disease.

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mHealth and wearable technology should replace motor diaries to track motor fluctuations in Parkinson's disease.

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