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Jari Ruokolainen

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Studies in Health Technology and Informatics|August 8, 2025
Remote Multimodal Study - Case: OM ChantJari Ruokolainen
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|November 17, 2018
Identification of Parkinson's Disease Utilizing a Single Self-recorded 20-step Walking Test Acquired by Smartphone's Inertial Measurement UnitSaeed Mehrang, Milla Jauhiainen, Julia Pietil, et al.
Studies in Health Technology and Informatics|June 8, 2022
Mobilemicroservices Architecture for Remote Monitoring of Patients: A Feasibility StudyJari Ruokolainen, Juan Haladijan, Milla Juutinen, et al.
Plos One|July 24, 2020
Parkinson's disease detection from 20-step walking tests using inertial sensors of a smartphone: Machine learning approach based on an observational case-control studyMilla Juutinen, Cassia Wang, Justin Zhu, et al.
JMIR Research Protocols|March 28, 2019
Identification of Motor Symptoms Related to Parkinson Disease Using Motion-Tracking Sensors at Home (KÄVELI): Protocol for an Observational Case-Control StudyMilla Jauhiainen, Juha Puustinen, Saeed Mehrang, et al.
Pageof 1

Showing results (1-10 of 5) with videos related to

Sort By:
Pageof 1
Studies in Health Technology and Informatics|August 8, 2025
Remote Multimodal Study - Case: OM ChantJari Ruokolainen
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|November 17, 2018
Identification of Parkinson's Disease Utilizing a Single Self-recorded 20-step Walking Test Acquired by Smartphone's Inertial Measurement UnitSaeed Mehrang, Milla Jauhiainen, Julia Pietil, et al.
Studies in Health Technology and Informatics|June 8, 2022
Mobilemicroservices Architecture for Remote Monitoring of Patients: A Feasibility StudyJari Ruokolainen, Juan Haladijan, Milla Juutinen, et al.
Plos One|July 24, 2020
Parkinson's disease detection from 20-step walking tests using inertial sensors of a smartphone: Machine learning approach based on an observational case-control studyMilla Juutinen, Cassia Wang, Justin Zhu, et al.
JMIR Research Protocols|March 28, 2019
Identification of Motor Symptoms Related to Parkinson Disease Using Motion-Tracking Sensors at Home (KÄVELI): Protocol for an Observational Case-Control StudyMilla Jauhiainen, Juha Puustinen, Saeed Mehrang, et al.
Pageof 1