Titlebook: Challenges and Trends in Multimodal Fall Detection for Healthcare; Hiram Ponce,Lourdes Martínez-Villase?or,Ernesto Mo Book 2020 Springer N

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Draft Agrarian Programme, July 1895features using an optical flow method that obtains information of relative motion between two consecutive images. For experimental results, we tested this approach in UP-Fall Detection dataset. Results showed that our proposed multi-vision-based approach detects human falls achieving 95.64% in accur

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Patient Relationship Managementelderly people’s quality of life, as they can read and analyze through sensors their facial expressions, voice, among others. Gamification in older people may motivate elderly people to socialize with their peers through social interaction and by doing activities as exercising. Thus, this chapter pr

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Wearable Sensors Data-Fusion and Machine-Learning Method for Fall Detection and Activity Recognitionhe 3 most similar users as the ones used for the test. The internal evaluation on the 9 users showed that with this optimized configuration the method achieves 98% accuracy. During the final evaluation for the challenge, our method achieved the highest results (82.5% F1-score, and 98% accuracy) and

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