Cargando…
Making Activity Recognition Robust against Deceptive Behavior
Healthcare services increasingly use the activity recognition technology to track the daily activities of individuals. In some cases, this is used to provide incentives. For example, some health insurance companies offer discount to customers who are physically active, based on the data collected fr...
Autores principales: | Saeb, Sohrab, Körding, Konrad, Mohr, David C. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4676610/ https://www.ncbi.nlm.nih.gov/pubmed/26659118 http://dx.doi.org/10.1371/journal.pone.0144795 |
Ejemplares similares
-
The need to approximate the use-case in clinical machine learning
por: Saeb, Sohrab, et al.
Publicado: (2017) -
Mobile Phone Detection of Semantic Location and Its Relationship to Depression and Anxiety
por: Saeb, Sohrab, et al.
Publicado: (2017) -
Relationship Between Sleep Quality and Mood: Ecological Momentary Assessment Study
por: Triantafillou, Sofia, et al.
Publicado: (2019) -
Mobile Phone Sensor Correlates of Depressive Symptom Severity in Daily-Life Behavior: An Exploratory Study
por: Saeb, Sohrab, et al.
Publicado: (2015) -
Authorship Correction: Scalable Passive Sleep Monitoring Using Mobile Phones: Opportunities and Obstacles
por: Saeb, Sohrab, et al.
Publicado: (2017)