Accelerometer data collected with a minimum set of wearable sensors from subjects with Parkinson’s disease

Parkinson’s disease (PD) is a neurodegenerative disorder associated with motor and non-motor symptoms. Current treatments primarily focus on managing motor symptom severity such as tremor, bradykinesia, and rigidity. However, as the disease progresses, treatment side-effects can emerge such as on/of...

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Published inScientific data Vol. 8; no. 1; pp. 48 - 13
Main Authors Daneault, Jean-Francois, Vergara-Diaz, Gloria, Parisi, Federico, Admati, Chen, Alfonso, Christina, Bertoli, Matilde, Bonizzoni, Edoardo, Carvalho, Gabriela Ferreira, Costante, Gianluca, Fabara, Eric Eduardo, Fixler, Naama, Golabchi, Fatemah Noushin, Growdon, John, Sapienza, Stefano, Snyder, Phil, Shpigelman, Shahar, Sudarsky, Lewis, Daeschler, Margaret, Bataille, Lauren, Sieberts, Solveig K., Omberg, Larsson, Moore, Steven, Bonato, Paolo
Format Journal Article
LanguageEnglish
Published London Nature Publishing Group UK 05.02.2021
Nature Publishing Group
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ISSN2052-4463
2052-4463
DOI10.1038/s41597-021-00830-0

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Abstract Parkinson’s disease (PD) is a neurodegenerative disorder associated with motor and non-motor symptoms. Current treatments primarily focus on managing motor symptom severity such as tremor, bradykinesia, and rigidity. However, as the disease progresses, treatment side-effects can emerge such as on/off periods and dyskinesia. The objective of the Levodopa Response Study was to identify whether wearable sensor data can be used to objectively quantify symptom severity in individuals with PD exhibiting motor fluctuations. Thirty-one subjects with PD were recruited from 2 sites to participate in a 4-day study. Data was collected using 2 wrist-worn accelerometers and a waist-worn smartphone. During Days 1 and 4, a portion of the data was collected in the laboratory while subjects performed a battery of motor tasks as clinicians rated symptom severity. The remaining of the recordings were performed in the home and community settings. To our knowledge, this is the first dataset collected using wearable accelerometers with specific focus on individuals with PD experiencing motor fluctuations that is made available via an open data repository. Measurement(s) body movement coordination trait • Movement Disorder Society Unified Parkinson’s Disease Rating Scale Questionnaire • Medication • motor coordination/balance trait • sleep pattern • MDS-UPDRS Tasks and Simulated Activities of Daily Living (in-clinic) • Activity of Daily Living Technology Type(s) Accelerometer • body movement/behavior method • Clinical Observation • smartphone • Subject Diary Factor Type(s) age of patient • gender of patient • timing of medication intake Sample Characteristic - Organism Homo sapiens Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.13342055
AbstractList Parkinson's disease (PD) is a neurodegenerative disorder associated with motor and non-motor symptoms. Current treatments primarily focus on managing motor symptom severity such as tremor, bradykinesia, and rigidity. However, as the disease progresses, treatment side-effects can emerge such as on/off periods and dyskinesia. The objective of the Levodopa Response Study was to identify whether wearable sensor data can be used to objectively quantify symptom severity in individuals with PD exhibiting motor fluctuations. Thirty-one subjects with PD were recruited from 2 sites to participate in a 4-day study. Data was collected using 2 wrist-worn accelerometers and a waist-worn smartphone. During Days 1 and 4, a portion of the data was collected in the laboratory while subjects performed a battery of motor tasks as clinicians rated symptom severity. The remaining of the recordings were performed in the home and community settings. To our knowledge, this is the first dataset collected using wearable accelerometers with specific focus on individuals with PD experiencing motor fluctuations that is made available via an open data repository.Parkinson's disease (PD) is a neurodegenerative disorder associated with motor and non-motor symptoms. Current treatments primarily focus on managing motor symptom severity such as tremor, bradykinesia, and rigidity. However, as the disease progresses, treatment side-effects can emerge such as on/off periods and dyskinesia. The objective of the Levodopa Response Study was to identify whether wearable sensor data can be used to objectively quantify symptom severity in individuals with PD exhibiting motor fluctuations. Thirty-one subjects with PD were recruited from 2 sites to participate in a 4-day study. Data was collected using 2 wrist-worn accelerometers and a waist-worn smartphone. During Days 1 and 4, a portion of the data was collected in the laboratory while subjects performed a battery of motor tasks as clinicians rated symptom severity. The remaining of the recordings were performed in the home and community settings. To our knowledge, this is the first dataset collected using wearable accelerometers with specific focus on individuals with PD experiencing motor fluctuations that is made available via an open data repository.
Measurement(s) body movement coordination trait • Movement Disorder Society Unified Parkinson’s Disease Rating Scale Questionnaire • Medication • motor coordination/balance trait • sleep pattern • MDS-UPDRS Tasks and Simulated Activities of Daily Living (in-clinic) • Activity of Daily Living Technology Type(s) Accelerometer • body movement/behavior method • Clinical Observation • smartphone • Subject Diary Factor Type(s) age of patient • gender of patient • timing of medication intake Sample Characteristic - Organism Homo sapiens Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.13342055
Parkinson's disease (PD) is a neurodegenerative disorder associated with motor and non-motor symptoms. Current treatments primarily focus on managing motor symptom severity such as tremor, bradykinesia, and rigidity. However, as the disease progresses, treatment side-effects can emerge such as on/off periods and dyskinesia. The objective of the Levodopa Response Study was to identify whether wearable sensor data can be used to objectively quantify symptom severity in individuals with PD exhibiting motor fluctuations. Thirty-one subjects with PD were recruited from 2 sites to participate in a 4-day study. Data was collected using 2 wrist-worn accelerometers and a waist-worn smartphone. During Days 1 and 4, a portion of the data was collected in the laboratory while subjects performed a battery of motor tasks as clinicians rated symptom severity. The remaining of the recordings were performed in the home and community settings. To our knowledge, this is the first dataset collected using wearable accelerometers with specific focus on individuals with PD experiencing motor fluctuations that is made available via an open data repository.
Parkinson’s disease (PD) is a neurodegenerative disorder associated with motor and non-motor symptoms. Current treatments primarily focus on managing motor symptom severity such as tremor, bradykinesia, and rigidity. However, as the disease progresses, treatment side-effects can emerge such as on/off periods and dyskinesia. The objective of the Levodopa Response Study was to identify whether wearable sensor data can be used to objectively quantify symptom severity in individuals with PD exhibiting motor fluctuations. Thirty-one subjects with PD were recruited from 2 sites to participate in a 4-day study. Data was collected using 2 wrist-worn accelerometers and a waist-worn smartphone. During Days 1 and 4, a portion of the data was collected in the laboratory while subjects performed a battery of motor tasks as clinicians rated symptom severity. The remaining of the recordings were performed in the home and community settings. To our knowledge, this is the first dataset collected using wearable accelerometers with specific focus on individuals with PD experiencing motor fluctuations that is made available via an open data repository. Measurement(s) body movement coordination trait • Movement Disorder Society Unified Parkinson’s Disease Rating Scale Questionnaire • Medication • motor coordination/balance trait • sleep pattern • MDS-UPDRS Tasks and Simulated Activities of Daily Living (in-clinic) • Activity of Daily Living Technology Type(s) Accelerometer • body movement/behavior method • Clinical Observation • smartphone • Subject Diary Factor Type(s) age of patient • gender of patient • timing of medication intake Sample Characteristic - Organism Homo sapiens Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.13342055
Parkinson’s disease (PD) is a neurodegenerative disorder associated with motor and non-motor symptoms. Current treatments primarily focus on managing motor symptom severity such as tremor, bradykinesia, and rigidity. However, as the disease progresses, treatment side-effects can emerge such as on/off periods and dyskinesia. The objective of the Levodopa Response Study was to identify whether wearable sensor data can be used to objectively quantify symptom severity in individuals with PD exhibiting motor fluctuations. Thirty-one subjects with PD were recruited from 2 sites to participate in a 4-day study. Data was collected using 2 wrist-worn accelerometers and a waist-worn smartphone. During Days 1 and 4, a portion of the data was collected in the laboratory while subjects performed a battery of motor tasks as clinicians rated symptom severity. The remaining of the recordings were performed in the home and community settings. To our knowledge, this is the first dataset collected using wearable accelerometers with specific focus on individuals with PD experiencing motor fluctuations that is made available via an open data repository. Measurement(s) body movement coordination trait • Movement Disorder Society Unified Parkinson’s Disease Rating Scale Questionnaire • Medication • motor coordination/balance trait • sleep pattern • MDS-UPDRS Tasks and Simulated Activities of Daily Living (in-clinic) • Activity of Daily Living Technology Type(s) Accelerometer • body movement/behavior method • Clinical Observation • smartphone • Subject Diary Factor Type(s) age of patient • gender of patient • timing of medication intake Sample Characteristic - Organism Homo sapiens Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.13342055
Parkinson’s disease (PD) is a neurodegenerative disorder associated with motor and non-motor symptoms. Current treatments primarily focus on managing motor symptom severity such as tremor, bradykinesia, and rigidity. However, as the disease progresses, treatment side-effects can emerge such as on/off periods and dyskinesia. The objective of the Levodopa Response Study was to identify whether wearable sensor data can be used to objectively quantify symptom severity in individuals with PD exhibiting motor fluctuations. Thirty-one subjects with PD were recruited from 2 sites to participate in a 4-day study. Data was collected using 2 wrist-worn accelerometers and a waist-worn smartphone. During Days 1 and 4, a portion of the data was collected in the laboratory while subjects performed a battery of motor tasks as clinicians rated symptom severity. The remaining of the recordings were performed in the home and community settings. To our knowledge, this is the first dataset collected using wearable accelerometers with specific focus on individuals with PD experiencing motor fluctuations that is made available via an open data repository.Measurement(s)body movement coordination trait • Movement Disorder Society Unified Parkinson’s Disease Rating Scale Questionnaire • Medication • motor coordination/balance trait • sleep pattern • MDS-UPDRS Tasks and Simulated Activities of Daily Living (in-clinic) • Activity of Daily LivingTechnology Type(s)Accelerometer • body movement/behavior method • Clinical Observation • smartphone • Subject DiaryFactor Type(s)age of patient • gender of patient • timing of medication intakeSample Characteristic - OrganismHomo sapiensMachine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.13342055
ArticleNumber 48
Author Carvalho, Gabriela Ferreira
Fixler, Naama
Daeschler, Margaret
Shpigelman, Shahar
Parisi, Federico
Golabchi, Fatemah Noushin
Bataille, Lauren
Snyder, Phil
Growdon, John
Sudarsky, Lewis
Sieberts, Solveig K.
Sapienza, Stefano
Moore, Steven
Bonizzoni, Edoardo
Fabara, Eric Eduardo
Alfonso, Christina
Daneault, Jean-Francois
Vergara-Diaz, Gloria
Bertoli, Matilde
Costante, Gianluca
Admati, Chen
Bonato, Paolo
Omberg, Larsson
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  organization: Department of Physical Medicine and Rehabilitation, Harvard Medical School, Spaulding Rehabilitation Hospital, Wyss Institute for Biologically Inspired Engineering, Harvard University
BackLink https://www.ncbi.nlm.nih.gov/pubmed/33547309$$D View this record in MEDLINE/PubMed
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Snippet Parkinson’s disease (PD) is a neurodegenerative disorder associated with motor and non-motor symptoms. Current treatments primarily focus on managing motor...
Parkinson's disease (PD) is a neurodegenerative disorder associated with motor and non-motor symptoms. Current treatments primarily focus on managing motor...
Measurement(s) body movement coordination trait • Movement Disorder Society Unified Parkinson’s Disease Rating Scale Questionnaire • Medication • motor...
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StartPage 48
SubjectTerms 692/617/375/1718
692/617/375/346/1718
Accelerometry - methods
Activities of daily living
Coordination
Data Descriptor
Dyskinesia
Humanities and Social Sciences
Humans
Levodopa
Medical treatment
Movement disorders
multidisciplinary
Neurodegenerative diseases
Parabrachial Nucleus
Parkinson Disease - diagnosis
Parkinson Disease - physiopathology
Parkinson's disease
Patients
Science
Science (multidisciplinary)
Sleep
Smartphone
Smartphones
Tremor
Wearable Electronic Devices
Wrist
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Title Accelerometer data collected with a minimum set of wearable sensors from subjects with Parkinson’s disease
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