M
Miikka Ermes
Researcher at VTT Technical Research Centre of Finland
Publications - 49
Citations - 2882
Miikka Ermes is an academic researcher from VTT Technical Research Centre of Finland. The author has contributed to research in topics: Randomized controlled trial & Acceptance and commitment therapy. The author has an hindex of 19, co-authored 48 publications receiving 2608 citations. Previous affiliations of Miikka Ermes include Flinders University & Nokia.
Papers
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Journal ArticleDOI
Activity classification using realistic data from wearable sensors
TL;DR: Methods used for classification of everyday activities like walking, running, and cycling are described to find out how to recognize activities, which sensors are useful and what kind of signal processing and classification is required.
Journal ArticleDOI
Detection of Daily Activities and Sports With Wearable Sensors in Controlled and Uncontrolled Conditions
TL;DR: The aim of this study was to examine how well the daily activities and sports performed by the subjects in unsupervised settings can be recognized compared to supervised settings and support a vision of recognizing a wider spectrum, and more complex activities in real life settings.
Journal ArticleDOI
Mobile Mental Wellness Training for Stress Management: Feasibility and Design Implications Based on a One-Month Field Study
Aino Ahtinen,Elina Mattila,Pasi Välkkynen,Kirsikka Kaipainen,Toni Vanhala,Miikka Ermes,Essi Sairanen,Tero Myllymäki,Raimo Lappalainen +8 more
TL;DR: A feasibility study of Oiva mobile mental wellness training app showed good acceptability, usefulness, and engagement among the working-age participants, and provided increased understanding on the essential features of mobile apps for stress management.
Journal ArticleDOI
Hypothermia-treated cardiac arrest patients with good neurological outcome differ early in quantitative variables of EEG suppression and epileptiform activity.
Johanna Wennervirta,Miikka Ermes,S Marjaana Tiainen,Tapani Salmi,Marja Hynninen,Mika Sarkela,Markku Hynynen,Ulf-Håkan Stenman,Hanna E. Viertio-Oja,Kari-Pekka Saastamoinen,Ville Pettilä,Anne Vakkuri +11 more
TL;DR: Quantitative electroencephalographic variables may be used to differentiate patients with good neurologic outcomes from those with poor outcomes after out-of-hospital cardiac arrest.
Proceedings ArticleDOI
Advancing from offline to online activity recognition with wearable sensors
TL;DR: The results suggest that earlier developed offline analysis methods for the acceleration data obtained from wearable sensors can be successfully implemented in an online activity recognition application.