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JMIR Formative Research|May 5, 2020
A Persuasive mHealth Behavioral Change Intervention for Promoting Physical Activity in the Workplace: Feasibility Randomized Controlled TrialMd Sanaul Haque, Maarit Kangas, Timo Jämsä
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|November 16, 2007
Determination of simple thresholds for accelerometry-based parameters for fall detectionMaarit Kangas, Antti Konttila, Ilkka Winblad, et al.
Gait & Posture|February 26, 2008
Comparison of low-complexity fall detection algorithms for body attached accelerometersMaarit Kangas, Antti Konttila, Per Lindgren, et al.
BMC Women'S Health|December 1, 2019
Nocturnal finger skin temperature in menstrual cycle tracking: ambulatory pilot study using a wearable Oura ringAnna Maijala, Hannu Kinnunen, Heli Koskimäki, et al.
Gerontology|August 21, 2014
Sensitivity and false alarm rate of a fall sensor in long-term fall detection in the elderlyMaarit Kangas, Raija Korpelainen, Irene Vikman, et al.
Gait & Posture|December 23, 2018
Calibration and validation of accelerometer-based activity monitors: A systematic review of machine-learning approachesVahid Farrahi, Maisa Niemelä, Maarit Kangas, et al.
Dementia (London, England)|October 27, 2016
Assistive technologies at home for people with a memory disorderLaura Nauha, Niina S Keränen, Maarit Kangas, et al.
Scandinavian Journal of Medicine & Science in Sports|April 3, 2021
Accumulation patterns of sedentary time and breaks and their association with cardiometabolic health markers in adultsVahid Farrahi, Maarit Kangas, Antti Kiviniemi, et al.
Health & Place|November 6, 2022
Residential history and changes in perceived health-The Northern Finland Birth Cohort 1966 studyTiina Lankila, Soile Puhakka, Mikko Kärmeniemi, et al.
IEEE Journal of Biomedical and Health Informatics|May 21, 2019
Evaluating and Enhancing the Generalization Performance of Machine Learning Models for Physical Activity Intensity Prediction From Raw Acceleration DataVahid Farrahi, Maisa Niemela, Petra Tjurin, et al.
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