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Limited By:	Subject = Human Activity Recognition;

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Displaying Results 1 - 3 of 3 on page 1 of 1

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Activity recognition of local muscular endurance (LME) exercises using an inertial sensor (2017)

Prabhu, Ghanashyama; Ahmadi, Amin; O'Connor, Noel E.; Moran, Kieran

Activity recognition of local muscular endurance (LME) exercises using an inertial sensor (2017)

Prabhu, Ghanashyama; Ahmadi, Amin; O'Connor, Noel E.; Moran, Kieran

Abstract:

In this paper, we propose an algorithmic approach for a motion analysis framework to automatically recognize local muscular endurance (LME) exercises and to count their repetitions using a wrist-worn inertial sensor. LME exercises are prescribed for cardiovascular disease rehabilitation. As a technical solution, we propose activity recognition based on machine learning. We developed an algorithm to automatically segment the captured data from all participants. Relevant time and frequency domain features were extracted using a sliding window technique. Principal component analysis (PCA) was applied for dimensionality reduction of the extracted features. We trained 15 binary classifiers using support vector machine (SVM) to recognize individual LME exercises, achieving overall accuracy of more than 98%. We applied grid search technique to obtain the optimal SVM hyperplane parameters. The learning curves (mean ± stdev) for each model is investigated to verify that the models were not o...

http://doras.dcu.ie/21887/

Marked Mark

Activity recognition of local muscular endurance (LME) exercises using an inertial sensor (2017)

Prabhu, Ghanashyama; Ahmadi, Amin; O'Connor, Noel E.; Moran, Kieran

Activity recognition of local muscular endurance (LME) exercises using an inertial sensor (2017)

Prabhu, Ghanashyama; Ahmadi, Amin; O'Connor, Noel E.; Moran, Kieran

Abstract:

http://doras.dcu.ie/22067/

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Smart lifelogging: recognizing human activities using PHASOR (2017)

Dao, Minh Son; Dang Nguyen, Duc Tien; Riegler, Michael; Gurrin, Cathal

Smart lifelogging: recognizing human activities using PHASOR (2017)

Dao, Minh Son; Dang Nguyen, Duc Tien; Riegler, Michael; Gurrin, Cathal

Abstract:

Lifelog, Human Activity Recognition, Smartphones, Embedded Sensors, Smart-City, Heterogeneous Sensory Data Analytics. This paper introduces a new idea for sensor data analytics, named PHASOR, that can recognize and stream individual human activities online. The proposed sensor concept can be utilized to solve some emerging problems in smartcity domain such as health care, urban mobility, or security by creating a lifelog of human activities. PHASOR is created from three ‘components’: ID, model, and Sensor. The first component is to identify which sensor is used to monitor which object (e.g., group of users, individual users, type of smart- phone). The second component decides suitable classifiers for human activities recognition. The last one includes two types: (1) physical sensors that utilize embedded sensors in smartphones to recognize human activities, (2) human factors that uses human interaction to personally increase the accuracy of the detection. The advantage of PHASOR is ...

http://doras.dcu.ie/21818/

Displaying Results 1 - 3 of 3 on page 1 of 1

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