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Large-Scale Wearable Sensor Deployment in Parkinson's Patients: The Parkinson@Home Study Protocol.

ABSTRACT: BACKGROUND:Long-term management of Parkinson's disease does not reach its full potential because we lack knowledge about individual variations in clinical presentation and disease progression. Continuous and longitudinal assessments in real-life (ie, within the patients' own home environment) might fill this knowledge gap. OBJECTIVE:The primary aim of the Parkinson@Home study is to evaluate the feasibility and compliance of using multiple wearable sensors to collect clinically relevant data. Our second aim is to address the usability of these data for answering clinical research questions. Finally, we aim to build a database for future validation of novel algorithms applied to sensor-derived data from Parkinson's patients during daily functioning. METHODS:The Parkinson@Home study is a two-phase observational study involving 1000 Parkinson's patients and 250 physiotherapists. Disease status is assessed using a short version of the Parkinson's Progression Markers Initiative protocol, performed by certified physiotherapists. Additionally, participants will wear a set of sensors (smartwatch, smartphone, and fall detector), and use these together with a customized smartphone app (Fox Insight), 24/7 for 3 months. The sensors embedded within the smartwatch and fall detector may be used to estimate physical activity, tremor, sleep quality, and falls. Medication intake and fall incidents will be measured via patients' self-reports in the smartphone app. Phase one will address the feasibility of the study protocol. In phase two, mathematicians will distill relevant summary statistics from the raw sensor signals, which will be compared against the clinical outcomes. RESULTS:Recruitment of 300 participants for phase one was concluded in March, 2016, and the follow-up period will end in June, 2016. Phase two will include the remaining participants, and will commence in September, 2016. CONCLUSIONS:The Parkinson@Home study is expected to generate new insights into the feasibility of integrating self-collected information from wearable sensors into both daily routines and clinical practices for Parkinson's patients. This study represents an important step towards building a reliable system that translates and integrates real-life information into clinical decisions, with the long-term aim of delivering personalized disease management support. CLINICALTRIAL:ClinicalTrials.gov NCT02474329; https://clinicaltrials.gov/ct2/show/NCT02474329 (Archived at http://www.webcitation.org/6joEc5P1v).

SUBMITTER: Silva de Lima AL

PROVIDER: S-EPMC5018102 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

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Large-Scale Wearable Sensor Deployment in Parkinson's Patients: The Parkinson@Home Study Protocol.

Silva de Lima Ana Lígia AL Hahn Tim T de Vries Nienke M NM Cohen Eli E Bataille Lauren L Little Max A MA Baldus Heribert H Bloem Bastiaan R BR Faber Marjan J MJ

JMIR research protocols 20160826 3

<h4>Background</h4>Long-term management of Parkinson's disease does not reach its full potential because we lack knowledge about individual variations in clinical presentation and disease progression. Continuous and longitudinal assessments in real-life (ie, within the patients' own home environment) might fill this knowledge gap.<h4>Objective</h4>The primary aim of the Parkinson@Home study is to evaluate the feasibility and compliance of using multiple wearable sensors to collect clinically rel ...[more]

PMID: 27565186

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Project description:INTRODUCTION:Exposure to poor environmental conditions has been associated with deterioration of physical and mental health, and with reduction of cognitive performance. Environmental conditions may also influence cognitive development of children, but epidemiological evidence is scant. In developed countries, children spend 930 hours per year in a classroom, second only to time spent in their bedroom. Using continuous sensing technology, we investigate the relationship between indoor environmental quality (IEQ) and cognitive performance of school-aged children. The proposed study will result in a better understanding of the effects of environmental characteristics on cognitive performance, thereby paving the way for experimental studies. METHODS AND ANALYSIS:A study protocol is presented to reliably measure IEQ in schools. We will monitor the IEQ of 280 classrooms for 5 years, covering approximately 10 000 children. Each classroom in the sample is permanently equipped with a sensor measuring air quality (carbon dioxide and coarse particles), temperature, relative humidity, light intensity and noise levels, all at 1 min intervals. The location of sensing equipment within and across rooms has been validated by a pilot study. Academic performance of school-aged children is measured through standardised cognitive tests. In addition, a series of health indicators is collected (eg, school absence and demand for healthcare), together with an extensive set of sociodemographic characteristics (eg, parental income, education, occupational status). ETHICS AND DISSEMINATION:Medical Ethical Approval for the current study was waived by the Medical Ethical Committee azM/UM (METC 2018-0681). In addition, data on student performance and health stems from an already existing data infrastructure that are granted with ethical approval by the Ethical Review Committee Inner City faculties (ERCIC_092_12_07_2018). Health data are obtained from the 'The Healthy Primary School of the Future' (HPSF) project. Medical Ethical Approval for HPSF was waived by the Medical Ethical Committee of Zuyderland, Heerlen (METC 14 N-142). The HPSF study protocol was registered in the database ClinicalTrials.gov on 14-06-2016 with reference number NCT02800616, this study is currently in the Results stage. Data collection from Gemeentelijke Gezondheidsdienst Zuid-Limburg (GGD-ZL) is executed by researchers of HPSF, this procedure has been fully approved by the Medical Ethical Committee of Zuyderland. The questionnaires on level of comfort will be filled in anonymously by students and teachers. The study will follow the EU General Data Protection Regulation (EU GDPR) and Dutch data protection law to ensure protection of personal data, as well as maintain proper data management and anonymisation.The protocol discussed in this paper includes significant efforts focused on integrating results and making them available to both the scientific community and the wider public, including policy makers. The results will lead to multiple scientific articles that will be disseminated through peer-reviewed international journals, as well as through conference presentations. In addition, we will exploit ongoing collaboration with project stakeholders and project partners to disseminate information to the target audience. For example, the results will be presented to school boards in the Netherlands, through engagement with the Coalition for Green Schools, as well as to school boards in USA, through engagement with the Center for Green Schools. TRIAL REGISTRATION NUMBER:NCT02800616; Results.

Project description:BackgroundParkinson disease (PD) symptoms are complex, gradually progressive, and fluctuate hour by hour. Home-based technological sensors are being investigated to measure symptoms and track disease progression. A smart home sensor platform, with cameras and wearable devices, could be a useful tool to use to get a fuller picture of what someone's symptoms are like. High-resolution video can capture the ground truth of symptoms and activities. There is a paucity of information about the acceptability of such sensors in PD.ObjectiveThe primary objective of our study was to explore the acceptability of living with a multimodal sensor platform in a naturalistic setting in PD. Two subobjectives are to identify any suggested limitations and to explore the sensors' impact on participant behaviors.MethodsA qualitative study was conducted with an inductive approach using semistructured interviews with a cohort of PD and control participants who lived freely for several days in a home-like environment while continuously being sensed.ResultsThis study of 24 participants (12 with PD) found that it is broadly acceptable to use multimodal sensors including wrist-worn wearables, cameras, and other ambient sensors passively in free-living in PD. The sensor that was found to be the least acceptable was the wearable device. Suggested limitations on the platform for home deployment included camera-free time and space. Behavior changes were noted by the study participants, which may have related to being passively sensed. Recording high-resolution video in the home setting for limited periods of time was felt to be acceptable to all participants.ConclusionsThe results broaden the knowledge of what types of sensors are acceptable for use in research in PD and what potential limitations on these sensors should be considered in future work. The participants' reported behavior change in this study should inform future similar research design to take this factor into account. Collaborative research study design, involving people living with PD at every stage, is important to ensure that the technology is acceptable and that the data outcomes produced are ecologically valid and accurate.International registered report identifier (irrid)RR2-10.1136/bmjopen-2020-041303.

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Large-Scale Wearable Sensor Deployment in Parkinson's Patients: The Parkinson@Home Study Protocol.

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Large-Scale Wearable Sensor Deployment in Parkinson's Patients: The Parkinson@Home Study Protocol.

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