METHOD FOR GENERATING A PERSONALIZED CLASSIFIER FOR HUMAN MOTION ACTIVITIES OF A MOBILE OR WEARABLE DEVICE USER WITH UNSUPERVISED LEARNING

METHOD FOR GENERATING A PERSONALIZED CLASSIFIER FOR HUMAN MOTION ACTIVITIES OF A MOBILE OR WEARABLE DEVICE USER WITH UNSUPERVISED LEARNING

Motion activity data is collected from at least one sensor. An initial motion activity classifier function is applied to the motion activity data to produce an initial motion activity posteriorgram. Pre-processing and segmenting the motion activity data into windows produces segmented motion activit...

Ausführliche Beschreibung

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Bibliographische Detailangaben
Hauptverfasser: BAHL, Rajendar, KUMAR, Arun, SINGH, Ghanapriya, CHOWDHARY, Mahesh
Format: Patent
Sprache:eng
Schlagworte:
DIAGNOSIS
HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA
HUMAN NECESSITIES
HYGIENE
IDENTIFICATION
INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS
MEDICAL OR VETERINARY SCIENCE
PHYSICS
SURGERY
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Beschreibung
Zusammenfassung:Motion activity data is collected from at least one sensor. An initial motion activity classifier function is applied to the motion activity data to produce an initial motion activity posteriorgram. Pre-processing and segmenting the motion activity data into windows produces segmented motion activity data from which sensor specific features are extracted. An updated motion activity classifier function is generated from the extracted sensor specific features. Subsequent motion activity data is also collected from the at least one sensor, and the updated motion activity classifier function is applied to the subsequent motion activity data to produce an updated motion activity posteriorgram.