Table 2.

Summary of relevant work on human digital twin generation using wearable sensors.

Ref	Objective	Wearable Used	Data Collected by Wearable	HDT Function
[8]	To utilize human digital twins to improve safety for workers in manufacturing systems	Inertial (MOCAP System)	Movement and position data from workers	Determine based on inertial data if a disturbance occurred in the workspace
[33]	To develop an affordable and user-friendly wearable system to produce human digital twins	Inertial (9-axis motion tracking system)	Tracks movement and position	Generates a human digital twin capable of tracking the subject’s movements and produces a 3D virtual model
[49]	To use ECG data to detect and predict heart conditions as they arise	ECG (through smart watches)	Heart rate to detect abnormalities such as arrhythmia	A digital twin was created based on ECG data that could identify and diagnose heart problems in real time for the patient
[57]	To generate a human twin that can be used to detect certain poses of the subject	Inertial (9-axis motion tracking system)	Measures orientation to detect certain poses	Generates a 3D model of a human arm based on movement data gathered from an IMU system on the subject’s arm
[58]	To utilize a wearable robotic exoskeleton to assist patients with arm movements during rehabilitation	EMG sensors within the robotic exoskeleton	Utilizes EMG sensors to measure muscle activity intent	Assists movements of the patient’s arm using a digital twin created from EMG data to detect muscle activation intent
[59]	To develop a smart clothing system that utilizes a variety of smart sensors to produce a digital twin of the wearer	MAX30102, MAX90614, WTGAHRS2, ATK1218-BD	Measures heart rate, blood oxygen levels, body temperature, movement, and position	Generates a human digital twin based on the wearer’s data collected from the wearable sensors and provides audio feedback and changes the temperature of the clothing
[44]	Review of novel wearables that have been used to generate digital twins	Various experimental IMU and EMG sensors	Measures movement and muscle activation	Digital twins created were able to measure the locomotion and position of the wearer based on movement from one part of the body
[51]	Utilizes human digital twins to analyze the fitness parameters of athletes to evaluate and predict performance	Fitbit Charge HR (heart rate sensor)	Measures heart rate data to record exercises and sleep activity	Human digital twins were created based on the athlete’s fitness data gathered from their Fitbit and inputted data through MyFitnessPal to predict exercise outcomes and offer recommendations on improving performance
[50]	To develop a user-friendly dashboard that can be used by informal caregivers to monitor the progress of stroke rehabilitation	sEMG (surface electromyography)	Measures muscle activation intent in the upper limb	Human digital twins were created based on sEMG that could monitor muscle activity in the upper limb during stroke rehabilitation
[68]	To develop a digital twin that represents a subject’s stress level primarily based on wearable sensors, phone usage, and social media activity	Smart watch (heart rate sensor and exercise tracker)	Measures heart rate data to form a correlation with phone and social media data to detect anxiety levels	The generated human digital twin could identify mental health conditions as they develop in response to stressors caused by COVID-19