Table 3 Shoulder motion monitoring for application in patients undergoing rehabilitation

Cutti 2008, [37]

Full-Text

M-IMU (n = 4),

Xsens MT9B

Unilateral:

Thorax (flat portion of the sternum), Scapula (central third, aligned with the cranial edge of the scapular spine), humerus (central third, slightly posterior), FA (distal)

Double-sided tape, elastic cuff

Sh ROM

(HT and ST joint angles)

RMSE = 0.2°-3.2°

VICON

Exp 1: elb FLX-EXT, PR-SU

sh FLX-EXT, IER, sh EL-DE and P-R

Exp 2: tasks in Exp1 + sh IER (arm abducted 90°), sh AB-AD (frontal plane),

HTN (sagittal and frontal plane)

HS (n = 1, M)

Develop a protocol to measure humerothoracic, scapulothoracic and elbow kinematics

Parel 2012, [65]

Full-Text

M-IMU (n = 3),

Xsens MTx

Unilateral:

thorax, scapula, humerus

Elastic cuff, adhesive

Sh ROM

(HT and ST joint angles)

–

Humerus FLX-EXT (sagittal plane) and AB-AD (scapular plane)

HS (n = 20)

7F, 13 M

28.3 ± 5.5 Y

P (n = 20)

8F, 12 M

43.9 ± 19.9 Y

Assess the inta- and inter-operator agreement of ISEO protocol in measuring scapulohumeral rhythm

Daponte 2013a, [66]

Conference

M-IMU (n = 2), Zolertia Z1

Unilateral:

UA, FA

Brace

Sh ROM

–

Sh AB-AD

Elb FLX

HS (n = 1)

Discuss design and implementation of a home rehabilitation system

Daponte 2013b, [67]

Conference

M-IMU (n = 2), Zolertia Z1

Unilateral:

UA, FA

Brace

Sh ROM,

Test1:

max gap =

6.5° (roll)

5.2° (pitch)

11.6° (yaw)

Test 1:

Tecno

Body MJS

Test 2: BTS

Test 1: shoulder IR, EL-DE and horizontal FLX-EXT

Test 2: elbow FLX-EXT (along sagittal and horizontal plane)

HS (n = 1, M)

Validation of a home rehabilitation system

Pan 2013, [68]

Full-Text

Acc (n = 2),

LIS3LV02DQ

Acc built-in a Smartphone (n = 1)

Unilateral:

-acc: UA, thorax

-Smartphone: wrist

Strap, Armband

Sh ROM

(HT joint angles)

–

Touch ear

Use fingers to climb wall

Pendulum clockwise and counter clockwise

Active-assisted stretch fore and side, raises hand from back

HS (n = 10)

3 M, 7 F

20-25Y

P (n = 14)

5 M, 9 F

44–67 Y

Describe design and implementation of a shoulder joint home-based rehabilitation monitoring system

Thiemjarus 2013, [69]

Conference

Acc (n = 1),

Analog Device

(acc: ADXL330)

Magn (n = 1),

Honeywell

(magn: HMC5843)

Unilateral:

UA (proximal) or wrist, left or right

Strap

Sh ROM,

RMSE = 0.86°-5.05°

–

Sh FLX-EXT, AB-AD, horizontal AB-AD, IER

HS, (n = 23)

20–55 Y

Evaluate the effect of sensor placement on the estimation accuracy of shoulder ROM

Rawashdeh 2015, [70]

Conference

M-IMU (n = 1),

InvenSense (gyr: ITG-3200)

Analog Device (acc: ADXL 345)

Honeywell (magn: HMC5883L)

Unilateral:

UA (lateral)

Strap

Sh ROM

–

7 sh rehabilitation exercises

2 sports activities

HS (n = 11)

Describe a detection and classification method of shoulder motion gestures that can be used to prevent shoulder injury

Álvarez 2016, [71]

Full-Text

M-IMU (n = 4),

Xsens MTx

Unilateral:

Back of the hand, FA (near wrist), UA (near elbow), back

Wristband, Velcro strap, elastic band

Sh ROM,

Lab test: mean error = 0.06° (FLX)

1.05° (lateral deviation)

Lab test:

robotic wrist

Test1: Mounting of a shock dumper system

Test2: holding a tablet for long periods

Test3: elbow FLX-EXT

Test1: Mechanical worker (n = 1)

Test2: worker of a commercial centre (n = 1)

Test3: patient (n = 1)

Demonstrate the feasibility of an IMU-based system to measure upper limb joint angles in occupational health

Lee 2016, [72]

Conference

Strain sensor (n = 2),

MWCNT, Hyosung: multi-walled carbon nanotubes, EcoFlex0030, Smooth-On: silicon rubber

Unilateral: Shoulder

Skin adhesive

Sh ROM, RMSE<10°

OptiTrack

Sh FLX-EXT

Sh AB-AD

HS (n = 1)

Validate sensors and calibration method estimating two shoulder joint angles

Tran e Vajerano 2016, [73]

Conference

M-IMU (n = 2),

Shimmer2r

Unilateral:

UA (distal, near elbow), FA (distal, near wrist)

Straps

Sh ROM

(HT joint angles)

–

Periodic arm movements

HS (n = 1)

Validate an algorithm to predict the received signal strength indicator (RSSI) and the future joint-angle values of the user

Rawashdeh 2016, [74]

Full-Text

M-IMU (n = 1),

InvenSense (gyr: ITG-3200)

Analog Device (acc: ADXL 345)

Honeywell (magn: HMC5883L)

Unilateral:

UA (central third)

Straps

Sh ROM

(HT motion)

Visual observation

7 sh rehabilitation exercises, baseball throws, volley serves

HS (n = 11)

25 ± 7 Y

Validate a detection and classification algorithm of upper limb movements

Wu 2016, [75]

Full-Text

M-IMU (n = 3), Bluetooth 3-Space Sensor, YEI

Unilateral: FA (near wrist), UA (near elbow), thorax (shifted to the right)

Strap, bandage

Sh ROM

(HT joint angles)

–

12 gestures common in daily life: 3 static and 9 dynamic

HS (n = 10)

9 M, 1 F

22–24 Y

Evaluate accuracy, recall and precision of a gesture recognition system

Burns 2018, [27]

Full-Text

Acc and gyr built-in a smartwatch (n = 1), Apple Watch (Series 2 &3)

Unilateral:

Wrist

Wristband

Sh ROM

–

Pendulum

AB

Forward EL

IR

ER

Trapezius EXT

Upright row

HS (n = 20)

14 M, 6 F

19–56 Y

Evaluate performance of a commercial smartwatch to perform home shoulder physiotherapy monitoring

Esfahani e Nussbaum 2018, [11]

Full-Text

Textile sensors (printed) n = 11

Bilateral:

Shoulder (n = 6), low back (n = 5)

Undershirt

Sh ROM, mean error = 9.6° for sh angle estimation

M-IMU (Xsens MTw Awinda)

Sh AB

Sh FLX-EXT

Sh IER

Left/right side bending

Trunk FLX-EXT

Trunk rot left/right

HS (n = 16),

10 M, 6 F

21.9 ± 3.3

Describe a smart undershirt and evaluate its accuracy in task classification and planar angle measures in the shoulder joints and low back

Ramkumar 2018, [76]

Full-Text

Acc,gyr and magn built-in a smartphone, Apple iPhone

Unilateral:

UA, FA

Armband

Sh ROM <5°

gon

AB (coronal plane)

forward FLX (sagittal plane)

IER (elbow fixed to the body flexed to 90°)

HS (n = 10)

5 M, 5 F

Mean 27 Y

Validate a motion-based machine learning software development kit for shoulder ROM