Limb and trunk accelerometer data collected with wearable sensors from subjects with Parkinson’s disease

• Published in: Scientific data Vol. 8; no. 1; pp. 47 - 12
• Main Authors: Vergara-Diaz, Gloria, Daneault, Jean-Francois, 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
• Language: English
• Published: London Nature Publishing Group UK 05.02.2021; Nature Publishing Group; Nature Portfolio
• Subjects: 692/617/375/1718; 692/617/375/346/1718; Accelerometers; Accelerometry - instrumentation; Activities of daily living; Coordination; Data Descriptor; Dyskinesia; Forearm; Humanities and Social Sciences; Humans; Laboratories; Leg; Mobile Applications; Monitoring, Ambulatory; Movement disorders; multidisciplinary; Neurodegenerative diseases; Parkinson Disease - diagnosis; Parkinson Disease - physiopathology; Parkinson's disease; Science; Science (multidisciplinary); Sensors; Sleep; Smartphone; Smartphones; Titration; Torso; Wearable Electronic Devices
• ISSN: 2052-4463; 2052-4463
• DOI: 10.1038/s41597-021-00831-z

Parkinson’s disease (PD) is a neurodegenerative disorder characterized by motor and non-motor symptoms. Dyskinesia and motor fluctuations are complications of PD medications. An objective measure of on/off time with/without dyskinesia has been sought for some time because it would facilitate the titration of medications. The objective of the dataset herein presented is to assess if wearable sensor data can be used to generate accurate estimates of limb-specific symptom severity. Nineteen subjects with PD experiencing motor fluctuations were asked to wear a total of five wearable sensors on both forearms and shanks, as well as on the lower back. Accelerometer data was collected for four days, including two laboratory visits lasting 3 to 4 hours each while the remainder of the time was spent at home and in the community. During the laboratory visits, subjects performed a battery of motor tasks while clinicians rated limb-specific symptom severity. At home, subjects were instructed to use a smartphone app that guided the periodic performance of a set of motor tasks. 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.13574279