Table 1 Clinical population studies

(1) Duc et al. 2014 [38]

20 subjects

Intervention:

10 patients with rotator cuff tear

Control:10 healthy subjects

Cross sectional

case control

(1) Quantifying the muscular activation duration in the upper trapezius, medial deltoid, and biceps brachii during movement

(2) Investigating the rotator cuff tear impression in both laboratory and daily life settings

Shoulders

(1) 2 IMU sensors of ADXRS and ADXL (triaxial gyroscope, and accelerometer) from Analog devices (Analog devices Inc., USA)

(2) 4 EMG sensors (Biometrics® SX230, UK) with sampling frequency of 1.6 kHz

(1) Duration of humorous movements (s)

(2) Duration of muscular activation (s) in medial deltoid and biceps brachii

No information

✓/×/×

(2) Pichonnaz et al. 2015 [45]

62 subjects

Intervention: 21 patients after rotator cuff surgery

Control: 41 healthy subjects

Longitudinal case control

[3, 6, and 12 months after surgery]

(1) Assessment of the underuse rate of relevance as an upper limb postsurgical function indicator

(2) Applying a new metric to investigate the effect of the rotator cuff surgery on arm usage during the first year after surgery

Shoulders

(1) 2 IMU modules each containing 3 ADXRS gyroscopes and 3 ADXL accelerometers (Analog Devices, Norwood, MA, USA)

(1) Arm activity usage (%)

No information

✓/×/×

(3) Duc. et al. 2013 [46]

Lab phase: 11 subjects

Clinical phase: 21 patients after rotator cuff surgery

Control: 41 healthy subjects

Longitudinal Case control [3, 6, and 12 months after surgery]

(1) Validating a method using wearable inertial sensors for detecting humerus movements relative to the trunk

(2) Providing new outcome parameters for arm movement during long-term measurement of daily activity

Shoulders

(1) 2 IMU modules each containing 3 ADXRS gyroscopes and 3 ADXL accelerometers (Analog Devices, Norwood, MA, USA)

(1) The movement frequency of arms (number of arm movements/ the number of sitting and standing hours)

(2) The symmetry index of Fr in dominant and non-dominant arms (%)

[Using duration of movements (h) and angular velocity of arms (°/s)]

No information

✓/×/×

(4) Najafi et al. 2021 [50]

29 subjects

Intervention: 16 neurogenic thoracic outlet syndrome (nTOS) patients

Control: 13 healthy subjects

Cross-sectional case control

(1) Identifying digital biomarkers of upper extremity function impacted by nTOS

(2) Using the biomarkers for objectively defining nTOS severity

Upper arm

(1) An IMU system (LEGSys™, BioSensics, Newton, MA, USA) attached using an adjustable strap (sampling frequency = 100 Hz)

(1) Joint angle, and angular velocity in 3 axes (yaw, pitch, roll; °, and °/s)

(2) Number of performed cycles

(3) Duration of abduction and adduction movements (ms)

MATLAB

×/×/×

(5) Van de Kleut. et al. 2021 [47]

33 subjects indicated for reverse total shoulder arthroplasty (RTSA)

Longitudinal case series

[1 month before surgery, and 3-month and 1-year after surgery]

(1) Proposing a new system to monitor and record arm motion and

activity at home preoperatively and postoperatively RTSA using portable wearable sensors

Shoulders

(1) 2 IMU sensors (3-Space Data Logger, Yost Labs, Portsmouth, OH,

USA, (sampling frequency = 10Hz) fitted in a tight-fitting compression shirt of Nike (Beaverton, OR, USA)

(1) Number of elevation events/h

(2) Percentage of time spent within different elevation ranges of 0◦–20◦, 20◦–40◦, 40◦–60◦, 60◦–80◦, 80◦–100◦, and > 100◦ (%)

(3) The percentage of occurred elevation events within the elevation ranges (%)

(4) Intensity of arm activity (low, moderate, or high)

[Using upper arm joint angles in 3 axes (yaw, pitch, roll; °)]

MATLAB

✓/×/×

(6) Kwak et al. 2019 [24]

24 patients with rotator cuff disease

Cross-sectional case series

(1) Measuring motion

smoothness–based parameters (motion quality) of the shoulder

(2) Proposing new parameters to discriminate between healthy shoulders and shoulders with rotator cuff tear

Wrist

(1) 1 IMU sensor (LogonU, Seoul, Republic of Korea) attached to the wrist using a stretchable fabric

(1) The number of peaks in the sum of angular velocity

(2) The peak velocity–to–mean velocity ratio (ratio of the maximum recorded angular velocity of the motion and the mean angular velocity)

(3) The number of sign reversals in angular velocity (number of zero crossings)

[Using angular velocity and acceleration of arms (°/s, g)]

MATLAB

×/×/×

(7) Larrivée et al. 2019 [25]

38 subjects affected by rotator cuff tendinopathy

Longitudinal case series [1 week before, the same day, 2 and 4 weeks after the

corticosteroid injection]

(1) Evaluation and comparison of test–retest reliability and sensitivity to change of clinical assessments of shoulder function to wrist-based inertial measures of shoulder motion

(2) determining the acceptability and

compliance of using wrist-based wearable sensors

Wrist of affected shoulder

Self-developed system called WIMU-GPS:

(1) 1 Wireless IMUs including GPS (SiRFstarIV, 48 Channels, sampled at 1Hz), (inertial data sampling frequency = 50 Hz) embedded in a fabric wrapping around the wrist

(1) Active time; reported as a ratio with total recording time (ratio)

(2) Mean activity count (AC) per minute (ratio) sorted in 3 categories of low-intensity (LIA), medium-intensity (MIA), and high-intensity activities (HIA)

[Using 3 axes acceleration data (g)]

No information

✓/✓/✓

(8) Burns et al. 2018 [26]

20 Healthy subjects

Cross-sectional case series

(1) Developing and evaluating the potential for performing home shoulder physiotherapy monitoring using a commercial smartwatch and a new classification method

Wrist

(1) Apple Watch (Series 2 & 3, Apple Inc., USA) containing 6-axis acceleration and gyroscope (sampling frequency = 50 Hz)

(1) Acceleration and rotational velocity in all 3 axes (yaw, pitch, roll; g, and °/s)

PowerSense app

✓/×/✓

(9) Burns et al. 2020 [27]

42 patients with rotator cuff pathology

Longitudinal case series [monthly visits for a year after treatment]

(1) Validity assessment of a wearable sensor system for evaluating participation and technique adherence

of shoulder exercise

(2) Quantifying the rate of home physiotherapy adherence, and its effect on recovery

(3) Designing a pilot test for an ethically conscious adherence-driven rehabilitation program specialized for each individual

Wrist

(1) A Huawei 2 smartwatch (Huawei

Technologies Co Ltd, China, sampling frequency = 50 Hz)

(1) Participation adherence rate (%)

over each 2-week interval of treatment

(2) shoulder active range of motion in 3 axes (yaw, pitch, roll; °)

No information

✓/×/✓

(10) Hurd et al. 2018 [28]

14 subjects undergoing Reverse Shoulder Arthroplasty (RSA)

Longitudinal case series

(1) Evaluating the changes in pain, self-reported function, and limb activity and their correlation and difference after RSA using subjective and wearable sensor-measured outcomes

Wrist and upper arm

2 Triaxial GT3XP-BTLE IMUs (ActiGraph, Pensacola,

Florida, USA, sampling frequency = 100

Hz) attached with Velcro straps

(1) Mean limb activity (m/s²/epoch)

(2) The activity frequency categorized in 3 levels of inactive, low, and high (%) [Using 3 axes accelerometer data (g)]

MATLAB

✓/×/×

(11) Ajcevic et al. 2020 [51]

13 subjects

Intervention:

6 subjects with adhesive capsulitis (frozen shoulder)

Control: 7 healthy subjects

Longitudinal case control [at the beginning of study and after 3 months]

(1) Investigating

the possibility of quantitative evaluation of capsulate-related

deficit versus healthy controls

(2) Assessment of treatment efficacy

by measurement of shoulder kinematic parameters using IMUs

Shoulder (scapula and humerus)

2 MTw wireless IMUs (Xsens Technologies, Netherlands) placed on an elastic cuff

(1) The range of

motion in elevation, and abduction movements of scapula and humerus (yaw, and pitch; °)

(2) Activation time of the scapula and humerus (s)

No information

×/×/×

(12) Chen et al. 2020 [44]

Reliability: 25 subjects [ 10 for control group and 15 with Adhesive Capsulitis

Effectiveness: 15 subjects [7 for home-based exercise and 8 for motion sensor–assisted]

Longitudinal case control [at the beginning of study and after 1, 2, and 3 months]

(1) Verifying the reliability and effectiveness of a treatment model using a wearable motion sensor device to assist AC patients by performing home-based exercises to improve training compliance and the accuracy of exercises

Upper arm and Wrist

(1) 1 Motion sensor device (BoostFix wearable

self-training kit, COMPAL Electronics Inc, Taipei, Taiwan) containing 6-axis

microelectromechanical systems attached to body parts with straps

(1) Active ROM and passive ROM of shoulder (yaw, pitch, roll; °)

(2) Exercise completion rates (%)

Doctor and patient apps developed by BoostFix

✓/×/×

(13) Aslani et al. 2018 [39]

7 Subjects

[6 healthy subjects and 1 subject with frozen shoulder]

Cross-sectional case series

(1) Developing and evaluating a single IMU accompanied by an EMG sensor for monitoring the 3D reachable workspace along with simultaneous measurement of deltoid muscle activity

Upper arm

(1) IMU sensor: 1 BNO055 (Adafruit, USA) attached with an adjustable band

(2) EMG sensor:

MyoWare Muscle Sensor

(1) Shoulder range of motion in Spherical coordinate (azimuthal angle and elevation angle) [Reference point: Top shoulder joint]

(2) RMS values of EMG amplitude (V)

MATLAB

×/×/✓

(14) Yin and Xu-2018 [29]

1 Healthy subject

Preliminary study

(1) Proposing a system to recognize the movements of patients that require upper limb rehabilitation like frozen shoulder patients

(1) Upper arms, forearms, and hands

(1) 6 IMU sensors embedded in a designed stretchable sleeve (No further details)

(1) Joint elevation angles in all 3 axes (yaw, pitch, roll; °)

Self-developed game through Microsoft® XNA game engine

✓/×/✓

(15) Xuedan et al. 2019 [42]

No information

Preliminary study

(1) Proposing new treatment of shoulder periarthritis using near-infrared light through stimulation of the acupuncture points on frozen shoulder

Shoulder (scapulohumeral area)

(1) High-power LEDs (800mW) with wavelength of 940nm (near infrared) mounted on flexible circuit boards were attached to a mesh vest by a nylon Velcro (voltage:1.4–1.7 V;

current:700–1000 mA)

(1) Peak optical power (W)

(2) peak optical density (mW/cm²)

Self-developed software

×/×/×

(16) Körver et al. 2014 [52]

Control: 100 healthy

subjects

Intervention: 15 patients with subacromial impingement syndrome

Longitudinal case control [at diagnosis and 5 years after diagnosis]

(1) Objective assessment of shoulder movements in patients with subacromial impingement syndrome at baseline and at five-year after treatment using inertial movement sensor measurements

Upper arm

(1) 1 Inertia-Link-2400-SK1 IMU sensor (MicroStrain, Inc., Williston, Vermont, USA) fixed with an adhesive patch

Upper arm accelerations and angular velocity or rate in 3 axes (yaw, pitch, roll; g, and °/s)

3DM-GX2 Software Development Kit

×/×/×

(17) Lorussi et al. 2019 [43]

10 Healthy subjects

Cross-sectional

case series

(1) Development of a shoulder physiotherapy application (called ShoulPhy) for shoulder impingement syndrome patients with the aims of (a) remote monitoring of the subject’s adherence to the program (b) providing a quantitative evaluation of the therapeutic activity and functional level (c) designing individualized exercises by the therapists

IMUs: Wrists

Strain: spine to shoulder (scapula)

(1) 2 IMUs (MTw; XSens, Netherlands) embedded in wearable straps; 1 textile strain sensor (optical detection of relative positions of markers is made by Smart DX 100 (BTS Bioengineering, USA)

(1) Shoulder and wrists joint angles in 3 axes (yaw, pitch, roll; °) with respect to standing position reference

(2) The measurements error of software in 3 axes (yaw, pitch, roll; °)

ShoulPhy (self-developed app)

✓/×/×

(18) Carmona-Ortiz et al. 2020 [53]

A healthy subject and a subject with Becker muscular dystrophy

Cross-sectional

case series

(1) The development of a fully portable, nonobtrusive, and wearable IMU-based motion measurement system called the ArmTracker tracking arm and torso kinematics during daily life

Upper arms and forearms

(1) 4 IMU sensors (BNO055, Bosch Sensortec GmbH, sampling frequency = 50 Hz) encapsulated in a 3D printed plastic case

(2) a microcontroller (Teensy 3.6, PJRC.COM, LLC.)

[All components are embedded in a Lycra shirt.]

(1) Arm and wrists joint angles and acceleration (yaw, pitch, roll; °, g)

MATLAB

✓/×/×

(19) Zucchi et al. 2020 [30]

40 subjects with distal radius fractures [20 treated

with Kirschner wire fixation and 20 subjects treated with volar plate fixation]

Cross-sectional case control

(1) Retrospective evaluation of wrist ROM for patients in recovery after Kirschner wire fixation and volar plate fixation surgical treatment, using an IMU thereby evaluating the presence of compensatory movements

(2) Assessment of the presence of muscle fatigue,

through sEMG

IMU: hand

EMG: upper arm

(1) IMU: a single IMU sensor (Fisiocomputer, Rome, Italy) attached to hand with a band

(2) sEMG: a multichannel Pocket Free EMG system (BTSengineering, USA, sampling frequency = 1000 Hz)

(1) Affected wrist ROM (°) and in percentages with respect to the unaffected wrist (%) through ulnar and radial deviation (yaw), flexion

and extension (pitch), and pronation and supination of forearm

(2) EMG amplitude (V)

Fisiocomputer, and BTSengineering software

×/×/×

(20) Perraudin et al. 2018 [31]

Intervention: 30 patients with osteoarthritis, rheumatoid arthritis, or psoriatic arthritis

Control: 15 healthy subjects

Cross-sectional case control

(1) The feasibility of performing unsupervised, correct, and consistent sit to stand tests at home

(2) Finding a model that can that demonstrate the relationship of the tests duration obtained from sensors to pain and stiffness

Wrist

1 ActiGraph GT9X IMU sensor (ActiGraph Inc., USA, sampling frequency = 30 Hz) mounted on a wristband

(1) The 3-axis accelerometer data (g), and its spherical coordinates (norm vector, azimuth in degrees, elevation in degrees)

(2) The duration of the 5 × STS tests (s)

(3) Adherence to the tests (%)

Self-developed smartphone app

✓/×/×

(21) Kassanos et al. 2019 [32]

No information

Preliminary study

(1) proposing a new design for (a) temperature sensing and heating capabilities for localized temperature measurements

(b) thermotherapy and closed-loop thermoregulation for

the arthritis patients

Wrist

(1) A flexible printed circuit (FPC) with a 50 μm thick, 26 mm wide and 188 mm long, and made from polyimide substrate (wrapped around the wrist)

Temperature of element placed on wrist (°c)

No information

×/×/×

(22) Murad et al. 2017 [33]

1 Healthy subject

Preliminary study

(1) Providing rehabilitation programs through music therapy for individuals with motor impairments using Motion Initiated Music Ensemble with Sensors (MIMES)

Wrist

(1) A smartwatch (no further details)

(1) 3 Axes accelerometer signals of wrist (yaw, pitch, roll; g)

No information

✓/×/✓

(23) Holland et al. 2020 [34]

Control: 17 healthy subjects

Intervention: 10 patients with hand arthritis

Cross sectional case control

(1) Evaluating the appropriateness of ‘‘arthritic’’ designed golf grips for patients with hand arthritis by assessment of total applied grip force and grip configuration (ROM) using 12 ‘‘arthritic’’ designed golf grips in golfers with and without hand arthritis

Force: fingers (tips of thumb,

index, middle, and ring fingers)

(1) FingerTPS system containing 3 sensors (Pressure Profile Systems, Los Angeles, CA, USA, sampling frequency = 50Hz)

(1) Forces at the distal palmar aspect of the thumb, index, middle, and ring finger of each participant’s trail hand (Pounds per square inch or psi)

(2) Grip configuration or ROM of the thumb and index fingers (°)

Dartfish Movement Analysis Software/ Chameleon Visualization Software

×/×/×

(24) Silişteanu et al. 2016 [36]

25 subjects

with the Carpal tunnel syndrome

Longitudinal case series [followed by a 30-day duration]

(1) Limiting the flexion/extension movement at the level of hand and fingers by using sensor gloves reducing the recovery time of Carpal

tunnel syndrome

Hand

(1) VPL Data Glove (Sun Microsystems Inc., USA) containing 14 optical sensors embedded in a fabric glove

(Secondary)

(1) The positions of fingers (no information regarding the details)

No information

×/×/×

(25) Connolly et al. 2018 [54]

9 Subjects with significant (not severe) pain in their hands

Cross-sectional

case series

(1) Development of a novel wireless smart glove called iSEG-Glove to facilitate objective accurate measurement of fingers joint movement

Fingers and hand

(1) iSEG-Glove system containing:

(a) 16 9-axes IMU sensors; MPU-9150 (TDK InvenSense, Japan)

(b) AVR32; UC3C 32 Bit Microcontroller

(1) ROM and angular velocity of finger joints (yaw, pitch, roll; °, °/s)

Self-developed GUI

×/×/✓

(26) Mack and min-2019 [37]

No information

Preliminary study

(1) Developing a wireless wearable wrist positions detection system that monitors symptoms of Carpal Tunnel Syndrome using flex sensors

Wrist

(1) 2 Capacitive resistance flex sensor and potentiometer (Spectra symbol, USA) embedded in a thin fabric glove

(2) Arduino Pro Mini; ATmega328 AVR microcontroller

Wrist angle (pitch, °)

MATLAB (Self-developed GUI)

×/×/✓

(27) O’Quigley et al. 2014 [35]

No information

Preliminary study

(1) Proposing a glove for home-monitoring of Rheumatoid Arthritis (RA) patients through assessment of finger joints movement

(2) Comparison of the proposed developed sensor glove based on piezo-resistive fabrics with a motion capture VICON Nexus system

Piezo-resistive: Fingers IMU: top of the hand

(1) 10 piezo-resistive sensor fabrics

(LR and LTT of Eeonyx, USA), and 1 IMU sensor (No further details) embedded in a glove

(2) Arduino Fio as the core processing unit

Finger joint angles (°)

Self-developed GUI

✓/×/✓

(28) Langohr et al. 2018 [48]

36 Subjects undergone shoulder arthroplasty

Control: the contra-

lateral asymptomatic joint of subjects

Cross sectional case control

(1) Determining the total daily shoulder motion of patients following TSA and RTSA

(2) Comparing the mobility of the arthroplasty shoulder with the asymptomatic joint

(3) Comparing the daily motion of TSA and RTSA shoulders

Upper arms, forearms, and torso

(1) 5 9-axes IMU sensors (YEI Technology, Portsmouth, OH, USA) embedded in sewn pockets of a stretchable shirt

(2) An external battery pack affixed to a belt

(3) a tight-fitting long-sleeved spandex shirt (Nike, Beaverton, OR, USA)

(1) ROM and shoulder joint angles (°)

(2) Percentage of time spent in different angle ranges of elevation and plane of elevation axes (%)

(3) Number of motions per hour in each angle range

LabVIEW (Self-developed GUI)

✓/×/×

(29) Haverstock et al. 2020 [49]

Control: 13 healthy subjects

Intervention:

33 Subjects undergone shoulder arthroplasties

Cross sectional case control

(1) Determining the

posture and cumulative elbow motion during one-day daily activities

(2) Comparing elbow motions of both dominant and nondominant

arms

Upper arms, forearms, and torso

(1) 5 9-axes IMU sensors (YEI Technology, Portsmouth, OH, USA) embedded in sewn pockets of a stretchable shirt

(2) An external battery pack affixed to a belt

(3) a tight-fitting long-sleeved spandex shirt (Nike, Beaverton, OR, USA)

(1) ROM and forearm joint angles in flexion/extension and pronation/supination postures (°)

(2) Percentage of time spent in different angle ranges (%)

(3) Number of elbow motions per hour in each angle range

LabVIEW (Self-developed GUI)

✓/×/×

(30) Lavado and Vela 2022 [40]

5 Healthy subjects

Cross-sectional

case series

(1) Design and implementation of an IMU- and EMG-based wearable device for telemonitoring the elbow flexion- extension angle and muscle activity of patients’ rehabilitation

IMU: Forearm

EMG: Upper arm (biceps brachii and triceps brachii)

(1) Gravity Analog EMG sensor (OYMotion, China)

(2) MPU-6050 (InvenSense Inc, USA);

a 3-axis gyroscope and a 3-axis accelerometer

(3) Arduino Nano as the core processing unit

(1) ROM and flexion–extension elbow joint angle (°)

(2) EMG amplitude of biceps brachii and triceps brachii (V)

MATLAB (Self-developed GUI)

×/×/✓

(31) Rigozzi et al. 2022 [41]

4 Healthy tennis players

Cross-sectional

case series

(1) Developing a novel microcontroller-based wearable device to measure grip strength, forearm EMG activity and vibrational transfer aiding the diagnose of elbow tendinopathy

(2) Comparing the grip strength and forearm EMG activity of tennis players with different levels of experience

EMG:

Forearm (extensor carpi radialis brevis and flexor carpi radialis)

Accelerometer: The racket, wrist (lateral epicondyle of the distal ulnar head) and elbow (lateral epicondyle of the humerus)

A prototype called TRAM-2 attached to the handle of racket:

(1) 2 EMG Muscle Sensors (MyoWare AT-04–001, Advancer Technologies, Raleigh, USA)

(2) 3 accelerometer sensors (ADXL377, SparkFun, Colorado, USA)

(3) a custom-built pressure sensor (Adafruit Velostat and Adafruit Copper Foil Sheet)

(4) a microcontroller (Teensy 3.6, PJRC, Oregon, USA)

(1) Normalized EMG activity and grip strength to the maximum voluntary contraction (MVC) activity level (%)

(2) Angular rotation of racket, wrist, and elbow (°/s)

No information

×/×/×