Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Machine Learning and Deep Learning in Human Activity Recognition and Fall Detection: Algorithms, Frameworks, and Applications for Sustainable Healthca

Machine Learning and Deep Learning in Human Activity Recognition and Fall Detection: Algorithms, Frameworks, and Applications for Sustainable Healthca

Biswas, Suparna

Hardcover

Series: Signals and Communication Technology

Medical ReferenceTechnology & Engineering

ISBN10: 303209240X
ISBN13: 9783032092403
Publisher: Springer
Published: Jan 3 2026
Pages: 146
Weight: 0.89
Height: 0.60 Width: 6.46 Depth: 9.38
Language: English
This book presents research into the domain of Human Activity Recognition (HAR) and Fall Detection (FD), with a focus on the seamless monitoring and support of elderly people. The author shows how current HAR and FD technologies have application in disease monitoring, prediction and identification, as well real-time facilitating early diagnosis of symptom-based disease identification, prediction, and detection. The author discusses existing infrastructure that supports this ecosystem, comprising smartphones, WiFi, 3G/4G Internet connectivity, and low-cost wearable sensors for sustainable health monitoring and care. The book presents smart technologies such as machine learning, deep learning, and Internet of Things that are applied for sensor data analysis and knowledge extraction towards accurate identification of activities and fall events with pre-fall postures in real time. The author also shows how smart and seamless health monitoring and care ecosystem fits with traditional healthcare system for sustainable solutions.

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