Activity, Behavior, and Healthcare Computing

Foreword

Preface

Acknowledgments

About the Editors

Part 1: Activity and Behavior

Chapter 1: PressureTransferNet: Human Attribute Guided Dynamic Ground Pressure Profile Transfer using 3D Simulated Pressure Maps

Chapter 2: SIMUAug: Variability-aware Data Augmentation for Wearable IMU using Physics Simulation

Chapter 3: Estimation of Muscle Activation during Complex Movement using Unsupervised Motion Primitives Decomposition of Limb Kinematics

Chapter 4: Pitcher Identification Method using an Accelerometer and Gyroscope Embedded in a Baseball

Chapter 5: Design and Implementation of a Long-Casting Support System for Lure Fishing using an Accelerometer

Chapter 6: Contrastive Left-Right Wearable Sensors (IMUs) Consistency Matching for HAR

Chapter 7: Estimation Method of Doneness for Boiled Eggs and Diced Steaks using Active Acoustic Sensing

Part 2: Healthcare

Chapter 8: Older Adults Daily Mobility and Its Connection to DEMMI

Chapter 9: Subjective Stress and Heart Rate Variability Patterns: A Study on Harassment Detection

Chapter 10: Analysis of Physiological Variances in Thermal Comfort among Individuals

Chapter 11: Personal Thermal Assessment using Feature Reduction and Machine Learning Techniques

Chapter 12: Analysis of Personal Thermal State using Machine Learning Algorithms to Prevent Heatstroke

Chapter 13: Ensemble Learning Models-Based Prediction of Personal Thermal Assessment Aimed at Heatstroke Prevention

Chapter 14: Predicting Heatstroke Risk and Preventing Health Complications: An Innovative Approach Using Machine Learning and Physiological Data

Chapter 15: Predictive Modeling for Heatstroke Risk Forecasting Integrating Physiological Features Using Ensemble Classifier

Chapter 16: Clustering-Based Feature Selection and Stacked Generalization Method to Offset Imbalanced Data for Thermal Stress Assessment

Chapter 17: Enhancing Personalized Heatstroke Prevention: Forecasting Thermal Comfort Sensations through Data-Driven Models

Chapter 18: Advancing Heatstroke Prevention: Integrating Physiological Data for Enhanced Thermal Comfort Forecasting

Chapter 19: Intrapatient Forecasting of Parkinsonâs Wearing-Off by Analyzing Data from Wrist-Worn Fitness Tracker and Smartphone

Chapter 20: Foreseeing Wearing-Off State in Parkinsonâs Disease Patients: A Multimodal Approach with the Usage of Machine Learning and Wearables

Chapter 21: Wearable Technology-Enabled Prediction of Wearing-Off Phenomenon in Parkinson's Disease: A Personalized Approach Using LSTM-Based Time-Series Analysis

Chapter 22: Forecasting Parkinsonâs Patientâs Wearing-Off Periods by Employing Stacked Super Learner

Chapter 23: Forecasting Wearing-Off in Parkinsonâs Disease: An Ensemble Learning Approach Using Wearable Data

Chapter 24: Forecasting the Wearing-Off Phenomenon in Parkinsonâs Disease: Summarized Approaches and Insights