Dataset Information

Continuous Monitoring of Essential Tremor Using a Portable System Based on Smartwatch.

ABSTRACT: Essential tremor (ET) shows amplitude fluctuations throughout the day, presenting challenges in both clinical and treatment monitoring. Tremor severity is currently evaluated by validated rating scales, which only provide a timely and subjective assessment during a clinical visit. Motor sensors have shown favorable performances in quantifying tremor objectively.A new highly portable system was used to monitor tremor continuously during daily lives. It consists of a smartwatch with a triaxial accelerometer, a smartphone, and a remote server. An experiment was conducted involving eight ET patients. The average effective data collection time per patient was 26 (±6.05) hours. Fahn-Tolosa-Marin Tremor Rating Scale (FTMTRS) was adopted as the gold standard to classify tremor and to validate the performance of the system. Quantitative analysis of tremor severity on different time scales is validated.Significant correlations were observed between neurologist's FTMTRS and patient's FTMTRS auto-assessment scores (r = 0.84; p = 0.009), between the device quantitative measures and the scores from the standardized assessments of neurologists (r = 0.80; p = 0.005) and patient's auto-evaluation (r = 0.97; p = 0.032), and between patient's FTMTRS auto-assessment scores day-to-day (r = 0.87; p < 0.001). A graphical representation of four patients with different degrees of tremor was presented, and a representative system is proposed to summarize the tremor scoring at different time scales.This study demonstrates the feasibility of prolonged and continuous monitoring of tremor severity during daily activities by a highly portable non-restrictive system, a useful tool to analyze efficacy and effectiveness of treatment.

SUBMITTER: Zheng X

PROVIDER: S-EPMC5350115 | biostudies-other | 2017

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Continuous Monitoring of Essential Tremor Using a Portable System Based on Smartwatch.

Zheng Xiaochen X Vieira Campos Alba A Ordieres-Meré Joaquín J Balseiro Jose J Labrador Marcos Sergio S Aladro Yolanda Y

Frontiers in neurology 20170315

<h4>Introduction</h4>Essential tremor (ET) shows amplitude fluctuations throughout the day, presenting challenges in both clinical and treatment monitoring. Tremor severity is currently evaluated by validated rating scales, which only provide a timely and subjective assessment during a clinical visit. Motor sensors have shown favorable performances in quantifying tremor objectively.<h4>Methods</h4>A new highly portable system was used to monitor tremor continuously during daily lives. It consist ...[more]

PMID: 28360883

Similar Datasets

Project description:BackgroundSleep disruption in critically ill adults can result in acute decrements in cognitive function, including delirium, but it is underdiagnosed in the setting of the intensive care unit (ICU). Although sleep stages can be assessed by polysomnography (PSG), acquisition and interpretation of PSG is costly, is labor intensive, is difficult to do over an extended period of time with critically ill patients (multiple days of continuous recording), and may interfere with patient care. In this pilot study, we investigated the feasibility and utility of monitoring sleep in the ICU setting using a portable electroencephalography (EEG) monitor, the SedLine brain monitor.MethodsWe first performed a baseline comparison study of the SedLine brain monitor by comparing its recordings to PSG recorded in a sleep laboratory (n = 3). In a separate patient cohort, we enrolled patients in the ICU who were monitored continuously with the SedLine monitor for sleep disruption (n = 23). In all enrolled patients, we continuously monitored their EEG. The raw EEG was retrieved and sleep stages and arousals were analyzed by a board-certified technologist. Delirium was measured by a trained research nurse using the Confusion Assessment Method developed for the ICU.ResultsFor all enrolled patients, we continuously monitored their EEGs and were able to retrieve the raw EEGs for analysis of sleep stages. Overall, the SedLine brain monitor was able to differentiate sleep stages, as well as capture arousals and transitions between sleep stages compared with the PSG performed in the sleep laboratory. The percentage agreement was 67% for the wake stage, 77% for the non-rapid eye movement (REM) stage (N1 = 29%, N2 = 88%, and N3 = 6%), and 89% for the REM stage. The overall agreement was measured with the use of weighted kappa, which was 0.61, 95% confidence interval, 0.58 to 0.64. In the ICU study, the mean recording time for the 23 enrolled patients was 19.10 hours. There were several signs indicative of poor-quality sleep, where sleep was distributed throughout the day, with reduced time spent in REM (1.38% ± 2.74% of total sleep time), and stage N3 (2.17% ± 5.53% of total sleep time) coupled with a high arousal index (34.63 ± 19.04 arousals per hour). The occurrence of ICU delirium was not significantly different between patients with and without sleep disruption.ConclusionsOur results suggest the utility of a portable EEG monitor to measure different sleep stages, transitions, and arousals; however, the accuracy in measuring different sleep stages by the SedLine monitor varies compared with PSG. Our results also support previous findings that sleep is fragmented in critically ill patients. Further research is necessary to develop portable EEG monitors that have higher agreement with PSG.

Project description:Essential tremor (ET) is among the most common neurological diseases and it often runs in families. How knowledgeable ET patients and their families are about their disease has been the subject of surprisingly little scholarship.To fill this gap in knowledge, we administered a comprehensive 32-item survey (i.e., questions about etiology, pathophysiology, symptoms and signs, natural history, and treatments) to 427 participants, including 76 ET probands, 74 affected relatives (AFRs), 238 unaffected relatives, and 39 spouses of unaffected relatives, all of whom were participating in two ET family studies. We hypothesized that there would be gaps in knowledge about ET and furthermore, that probands and AFRs would be the most knowledgeable, followed by unaffected relatives and then spouses of unaffected relatives, who would be the least knowledgeable.Overall, ET patients lacked knowledge about their disease. Nearly one-third of probands answered "yes" or "do not know" to the question, "is ET the same or different from the type of tremor that many normal people can get when they become old and frail?" A similar proportion did not know whether children could get ET or they responded "no." Nearly one-fourth of affecteds (i.e., probands and AFRs) did not know whether or to what degree (e.g., very well, moderately well, not well) the symptoms of ET could be medically controlled, and 38.0% either reported that there was no brain surgery for ET or reported that they did not know. Nearly 17% of affecteds did not endorse genes as a cause for ET, which was surprising given the fact that this was a family study of ET. Probands and AFRs were the most knowledgeable, followed by unaffected relatives. Spouses of unaffected relatives were the least knowledgeable.We targeted a large group of ET patients and their families, as this group is perhaps most likely to be informed about the disease. ET patients and their AFRs were more knowledgeable about the features of ET than their family members without ET. Overall, however, knowledge of ET was very limited and this lack of knowledge encompassed all aspects of the disease including its underlying causes, the nature of the symptoms and signs, its natural history and its treatment. Further ET awareness education and programs targeting both families of ET patients and the public would help alleviate this gap in knowledge.

Dataset Information

Continuous Monitoring of Essential Tremor Using a Portable System Based on Smartwatch.

Publications

Continuous Monitoring of Essential Tremor Using a Portable System Based on Smartwatch.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets