Low energy physical activity recognition system on smartphones. - Wikidata - wikimedia - TriplyDB

Low energy physical activity recognition system on smartphones.

Low energy physical activity recognition system on smartphones.

http://www.wikidata.org/entity/Q33442964

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A Review of Wearable Technologies for Elderly Care that Can Accurately Track Indoor Position, Recognize Physical Activities and Monitor Vital Signs in Real Time.Exercise Performance Measurement with Smartphone Embedded Sensor for Well-Being Management.Smartphone Location-Independent Physical Activity Recognition Based on Transportation Natural Vibration Analysis Energy-Efficient Crowdsensing of Human Mobility and Signal Levels in Cellular Networks.Hierarchical Activity Recognition Using Smart Watches and RGB-Depth Cameras A Comparison Study of Classifier Algorithms for Cross-Person Physical Activity Recognition.Pre-Processing Effect on the Accuracy of Event-Based Activity Segmentation and Classification through Inertial Sensors.A Novel Energy-Efficient Approach for Human Activity Recognition.

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P2860

Low energy physical activity recognition system on smartphones.

http://www.wikidata.org/entity/Q33442964

description

2015 nî lūn-bûn

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2015 թուականի Մարտին հրատարակուած գիտական յօդուած

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2015 թվականի մարտին հրատարակված գիտական հոդված

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2015年の論文

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2015年論文

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2015年論文

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2015年論文

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2015年論文

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2015年論文

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2015年论文

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Low energy physical activity recognition system on smartphones.

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Low energy physical activity recognition system on smartphones.

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Juan Antonio Ortega Ramirez

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Luis Miguel Soria Morillo

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Miguel Angel Alvarez de la Concepcion

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P2860

Multimodal physical activity recognition by fusing temporal and cepstral information.

Activity recognition using hybrid generative/discriminative models on home environments using binary sensors.

Physical activity and risk of stroke in women.

Activity identification using body-mounted sensors--a review of classification techniques.

Physical activity and coronary heart disease in women: is "no pain, no gain" passé?

Activity recognition of assembly tasks using body-worn microphones and accelerometers.

Body movement activity recognition for ambulatory cardiac monitoring.

A triaxial accelerometer-based physical-activity recognition via augmented-signal features and a hierarchical recognizer.

Comparative study on classifying human activities with miniature inertial and magnetic sensors

ISWC 2010: The Latest in Wearable Computing Research

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3

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Luis Gonzalez-Abril

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