03824nam 22006135 450 991104918710332120260102122902.03-032-09241-810.1007/978-3-032-09241-0(CKB)44769875100041(MiAaPQ)EBC32470442(Au-PeEL)EBL32470442(DE-He213)978-3-032-09241-0(EXLCZ)994476987510004120260102d2026 u| 0engur|||||||||||txtrdacontentcrdamediacrrdacarrierMachine Learning and Deep Learning in Human Activity Recognition and Fall Detection Algorithms, Frameworks, and Applications for Sustainable Healthcare /by Suparna Biswas1st ed. 2026.Cham :Springer Nature Switzerland :Imprint: Springer,2026.1 online resource (181 pages)Signals and Communication Technology,1860-48703-032-09240-X Introduction -- Introduction to Human Activity Recognition, Fall Monitoring and Detection, Health monitoring -- Fundamental concepts -- Machine Learning in Human Activity Recognition using Smartphone Sensors -- Deep Learning in Human Activity Recognition using Smartphone Sensors -- Machine Learning in Fall Detection System -- Sensor Fusion based HAR for Disease Monitoring and Prediction -- Design, Development, Deployment Strategies -- Conclusion.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. Presents smart technologies for sustainable health monitoring and care targeted for the elderly; Discusses techniques for privacy surrounding Human Activity Recognition (HAR) and Fall Detection (FD); Includes case studies, scenario-based studies, sponsored projects, prototypes and successful applications.Signals and Communication Technology,1860-4870TelecommunicationMedical informaticsSignal processingMachine learningCommunications Engineering, NetworksHealth InformaticsSignal, Speech and Image ProcessingMachine LearningTelecommunication.Medical informatics.Signal processing.Machine learning.Communications Engineering, Networks.Health Informatics.Signal, Speech and Image Processing.Machine Learning.621.382Biswas Suparna1886190MiAaPQMiAaPQMiAaPQBOOK9911049187103321Machine Learning and Deep Learning in Human Activity Recognition and Fall Detection4522304UNINA