Table 3 General wearable design/performance studies

(1) Hong et al. 2021 [87]

Subjects at risk of developing MSK disorders

Preliminary study

(1) Proposing a kirigami-structured highly anisotropic piezoelectric network composite (HAPNC) sensor for monitoring multiple information of joint motions, and sending an alarm to prevent MSK disorders

Shoulders

Multilayer HAPNC sensor: a cross-shaped polyethylene terephthalate (PET) substrate, with a square top and bottom layer with two electrodes

and one piezoelectric composite

(1) Bending angle (°) (2) Bending radius (mm)

(3) Voltage recorded from sensors movement (mV)

Self-developed software/ COMSOL Multiphysics

×/×/×

(2) Jang et al. 2020 [99]

28 Healthy subjects

Cross-sectional case series

(1) Proposing a novel method for monitoring bad postures, including the forward head posture, rounded shoulder, and elevated shoulder

Upper arms

2 IMU sensors of EBIMU24GV3 (E2BOX. China), embedded in a self-designed wearable fixture tool (made by a 3D printer) that can be wrapped around the shoulder (sampling frequency = 10 Hz)

The shoulder symmetry angl represented by percentage (%)

[Using elevation angle of shoulders (°)]

No information

×/×/×

(3) Matiur Rahman et al. 2021 [97]

10 Healthy subjects

Cross-sectional case series

(1) Identifying and discriminating subject-specific EMG signal patterns between five elbow joint angles (0°, 30°, 60°, 90° and 120°) during MVCs of sEMG

Upper arms

(1) A wearable 3 channel-based EMG system of SH-SHIM-KIT-004 (SHIMMER™, Ireland) with 1-kHz sampling rate

(2) Wet Ag/AgCl surface electrodes in bipolar setting and diameter of 4 mm

(1) sEMG signal (V)

MATLAB

×/×/×

(4) Zabat et al. 2015 [88]

1 Healthy athlete

Preliminary study

(1) Proposing an embedded system that measures joint

angles in 3 axes using gravitational acceleration and magnetic field sensors

measurements

Upper arm

(1) 1 LSM303DLHC sensor (STMicroelectronics Inc., Italy) containing a 3-axis digital accelerometer and magnetometer embedded in a prototype box package

(2) PIC18f2550 microcontroller

Flexion/extension, abduction/adduction and internal/external

rotations of the upper limb joint angles (yaw, pitch, and roll; °)

Self-developed GUI with Microsoft Visual C# (.NET Framework)

×/×/×

(5) Romero avilla et al. 2020 [96]

10 Healthy subjects

Cross-sectional case series

(1) Demonstrating the proof-of-principle of an innovative sEMG sensor system, independently used by patients for detecting their muscular activation

Upper arm and forearm (arranged circularly)

(1) 8 EMG modules each containing two bipolar sEMG leads equipped with seven dry cap-electrodes; embedded in a rotation-symmetrical flexible armband

(2) ARM microcontroller

(EFM32WG 380 F 256, Silicon Labs)

(1) RMS values EMG signal (mV)

No information

✓/×/×

(6) Jurioli et al. 2020 [98]

16 Healthy subjects

Cross-sectional case series

(1) Introducing a low-cost wearable device integrated to VR environments aiming to provide a better-quality rehabilitation process for most patients with motor disabilities

Forearm

(1) 1 IMU sensor of MPU-6050 (InvenSense Inc, USA)

(2) Arduino Nano microcontroller

(3) All instruments encapsulated in a 3D printed box made using ABS

(Acrylonitrile Butadiene Styrene) plastic and wrapped around the forearm with Velcro tapes

(1) Wrist positions in relation to the elbow (yaw, and roll, °)

(2) Time spent for completing the puzzle game (s)

Self-developed smartphone application

×/✓/✓

(7) Elshafei and Sheihab 2021 [89]

20 Healthy gym-goers

Cross-sectional case series

(1) Adopting a wearable approach for detecting biceps muscle fatigue during a bicep concentration curl exercise using an IMU wearable sensor

Wrist

1 IMU (Apple Watch Series 4, Apple Inc., USA) with sampling frequency of 50 Hz

(1) X-axis and Z-axis angular velocity and posture (°/s, °), Y-axis of accelerometer (g)

(2) Total exerted force of hand (N) [using product of used dumbbells mass and acceleration]

No information

×/×/✓

(8) Karunarathne and Pathirana 2014 [100]

4 Healthy subjects

Cross-sectional case series

(1) Investigating the applicability of some typical solutions of Wahba’s Problem and ordinary filtering mechanism with IMU sensor measurements for obtaining precise kinematics of human

Elbow and wrist of left arm

2 BioKin IMU sensors (BioKin Inc., Australia)

(1) The Root Mean Square Error (RMSE) of measured angles in both methods of IMUs and VICON motion capture (°) [Using wrist and elbow joint angles, accelerations, and velocities (yaw, pitch, roll; °, °/s, g)]

No information

×/×/✓

(9) Young et al. 2021 [101]

10 Healthy subjects

Cross-sectional case series

(1) Quantifying the accuracy and evaluating the validity of a novel proposed design to assess wrist ROM with respect to optical motion capture system as a gold standard through calculating their correlation coefficient

Wrist

(1) The set (3D printed in polylactic acid); contains 2 rotary position sensor of Bourns Model 3382 (Bourns, Riverside, CA, USA) embedded in the wrist strap

(2) Teensy 3.5 microcontroller (PJRC, Sherwood, OR)

(3) VICON motion capture system using 5 T160 and 4 Bonita cameras (Vicon Motion Systems Ltd., UK)

(1) Wrist flexion/extension and radial/ulnar deviation angles (pitch, yaw; °)

Python

×/×/×

(10) Hochman et al. 2020 [94]

7 Healthy subjects

Cross-sectional case series

(1) Proposing a novel method of measuring the joint acoustic emission of wrist using acoustic emission sensing method

Accelerometers: wrist

IMU: hand

(1) 4 Uniaxial accelerometers of 3225F7 (Dytran Instruments Inc., USA) used as contact microphones

(2) USB-4432 data acquisition (National Instruments, USA)

recording vibrations at a sampling rate of 50 kHz

(3)1 BNO-055 IMU package (Ardafruit Industries Inc., USA; Sampling frequency = 100 Hz) embedded in a silicone gel grip

(1) The signal-to-noise ratio (db) of recorded signal of microphones (uniaxial-accelerometer)

(2) Wrist angle and acceleration in 3 axes (yaw, pitch, roll; °)

MATLAB

×/×/×

(11) Saito et al. 2017 [90]

No information

Preliminary study

(1) Introducing a novel strain sensor using pyrolytic graphite sheet (PGS), a low-cost, simple, and flexible material, for the application of wearable devices for monitoring human activity

Elbow and middle finger

(1) Small and thin films are cut from 17-µm-thick PGSs, and then attached to a flexible plastic substrate

(2) Silver conducting paste as electrodes are wired on the films for electrical measurements, and the adhesives cover the silver electrodes for mechanical failure prevention

(1) Flexion/extension motion of elbow and fingers through mapping the resistance of the strain sensor (Ω)

No inforamtion

×/×/×

(12) Xie et al. 2020 [95]

No information

Preliminary study

(1) Proposing a novel method of monitoring biomechanical motion of joints (or eye blinking) based on electromagnetic sensing techniques

Index finger and wrist

(1) A self-developed high-speed Electromagnetic testing instrument based on Field Programmable Gate Array (FPGA), performing digital demodulation at 100 k/second and features an Ethernet communication

(2) Electromagnetic coils (the excitation coil driven by an alternating current ∼48 mA rms)

(1) Finger and wrist bending level and frequency through EM impedance (Ω)

No information

×/×/×

(13) Smondrk et al. 2021 [91]

1 Healthy subject

Preliminary study

(1) Designing and realizing a device for measurement of finger flexion, and extension and forearm motion

(2) Assessment of the device reliability

Bend sensor: fingers

IMU: forearm

(1) 5 Flexible bend sensors (Flexpoint Sensor Systems, USA) embedded inside the instrumented glove

(2) A 9-axis IMU, LSM9DSO (ST Microelectronics, Switzerland)

(3) A microcontroller unit of ATmega328P (Microchip Technology, USA)

(1) Fingers joint angles (pitch, °)

No information

×/×/✓

(14) Zheng et al. 2016 [92]

5 Healthy subjects

Cross-sectional case series

(1) Developing a sensor glove (called FuncAssess) and evaluation of its validity and reliability

(2) Proposing a method for visualizing and quantifying the abnormality of the inter-joint coordination

Fingers

(1) Glove fabric made from polyamide stretchable fabric including sleeves for insertion of force sensors

(2) 10 Bend sensors of Flexpoint Sensor Systems (Draper, USA, sampling frequency = 50 Hz)

(3) 5 Force sensors of Flexiforce (Tekscan, Inc., USA)

(4) MSP430 microcontroller (Texas Instruments, Inc., Dallas, TX)

(1) Finger joints bending angle (°)

(2) Finger joints load (gram)

MATLAB

×/×/×

(15) Moreira et al. 2014 [102]

1 Healthy subject

Preliminary study

(1) Proposing a glove aiming to (a) track hand and fingers, while minimizing drift and offset errors (b) avoid the need for cumbersome calibration procedures and (c) evaluate its reliability and validation

Hand and fingers

(1) Glove fabric is made from polyamide stretchable fabric

(2) 11 9-DOF IMUs including a 3-axis gyroscope sensor of L3GD20, STMicroelectronics Inc., Italy) and 3-axis accelerometer and magnetometer sensor of LSM303DLHC (STMicroelectronics Inc., Italy), all stitched to the fabric with four fixation points

(2) STM32F4 ARM processor

(1) Fingers and hand joint angles (yaw, pitch, and roll; °)

Python

×/×/✓

(16) Hazman et al. 2020 [103]

10 Healthy subjects

Cross-sectional case series

(1) Developing a glove for finger joint measurement for collecting ROM values of distal interphalangeal (DIP), proximal interphalangeal (PIP) and metacarpophalangeal (MCP) joints of an index finger

Index finger

The proposed glove:

(1) Made from cloth material

(1) 3 6-axis IMUs,

(2) 2 2.2-inch bend sensors,

(3) Arduino Nano (AVR microcontroller- ATMega328)

(1) ROM of the MCP, DIP, PIP joints in angles (yaw, pitch, and roll; °)

(2) Percentage of error between both methods (%)

A self-developed GUI on MATLAB

×/×/×

(17) Oigawa et al. 2021 [93]

2 Healthy subjects

Cross-sectional case series

(1) Investigating a novel method for evaluating hand movement function through fingertip data during a 10-s grip and release acquired by wearable contact-force and accelerometer sensors

Fingers

(1) 2 Contact-force sensors of HapLog (Kato Tech Co., Ltd., Kyoto, Japan) each containing

(a) a triaxial accelerometer

and a strain sensor mounted on the cover sensor

(b) a bangle-type connector

(c) a calibration unit

(1) 3 Axes, and absolute acceleration (yaw, pitch, roll; g)

(2) Contact force (N)

HapLog software

×/×/×/

(18) Rovini et al. 2020 [104]

20 Healthy subjects

Cross-sectional case series

(1) Proposing an innovative, ring-shaped wearable system, called SensRing, that provides inertial data of fingers during the movement

(2) Performing a preliminary technical validation to compare the measured data of the SensRing to a motion capture system of Vicon (as the gold standard) on two finger tapping exercises

Fingers

(1) SensRing: a ring-shaped wearable sensor, including

(a) a LSM9DS1 IMU sensor (STMicroelectronics, Italy, sampling frequency = 50 Hz)

(b) STM32-F103 ARM microcontroller (STMicroelectronics, Italy) [The processing board and device are fixed to the wrist with an elastic band]

(2) The Vicon system including 8 cameras (sampling frequency = 100Hz)

(1) Triaxial accelerations and

angular velocities (yaw, pitch, roll; g, °/s)

(2) Number of repetitions, frequency

of the movement (Hz), and range of index finger movement (°)

No information

×/×/✓