J
Juho Merilahti
Researcher at VTT Technical Research Centre of Finland
Publications - 25
Citations - 407
Juho Merilahti is an academic researcher from VTT Technical Research Centre of Finland. The author has contributed to research in topics: Actigraphy & Rehabilitation. The author has an hindex of 9, co-authored 25 publications receiving 363 citations.
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Journal ArticleDOI
Mobile Diary for Wellness Management—Results on Usage and Usability in Two User Studies
Elina Mattila,Juha Pärkkä,Marion Hermersdorf,Jussi Kaasinen,J. Vainio,Kai Samposalo,Juho Merilahti,J. Kolari,Minna Kulju,Raimo Lappalainen,Ilkka Korhonen +10 more
TL;DR: The results indicate that the WD is well suited for supporting CBT-based wellness management and considered as easy to use and useful in wellness management.
Journal ArticleDOI
Compliance and technical feasibility of long-term health monitoring with wearable and ambient technologies.
Juho Merilahti,Juha Pärkkä,Kari Antila,Paula Paavilainen,Elina Mattila,Esko-Juhani Malm,Ari Saarinen,Ilkka Korhonen +7 more
TL;DR: The study suggests that the data-collection rate is likely be 70–90% for typical health monitoring data and the users gave positive feedback in almost all their responses in a questionnaire.
Journal ArticleDOI
Wearable Monitoring of Physical Functioning and Disability Changes, Circadian Rhythms and Sleep Patterns in Nursing Home Residents
TL;DR: In this paper, the authors analyzed whether physical functioning status (Activities of Daily Living assessment of Resident Assessment Instrument) is associated with diurnal activity rhythm and sleep patterns measured with wearable activity sensor in nursing home residents during their normal daily life.
Proceedings ArticleDOI
Long-Term Subjective and Objective Sleep Analysis of Total Sleep Time and Sleep Quality in Real Life Settings
TL;DR: This study analyzed visually long- term sleep data collected with actigraphy, sleep logs and ambient sensors to gain more reliable results and compared these results to each single method's output.
Journal ArticleDOI
Accelerometry-Based Berg Balance Scale Score Estimation
TL;DR: The proposed gait-based method can identify subjects with high or low risk of falling with an accuracy of 77.8% and 96.6%, respectively, and the BBS-task based method with corresponding accuracy of 89.5% and 62.1%.