. 2023 Jul 19;23(14):6535. doi: 10.3390/s23146535

Table 5.

Studies that measured elbow joint angles using IMUs, including their sample size, study quality, sensor-to-segment calibration method, sensor-fusion approach, joint-angle calculation method, tasks performed, kinematic errors, and associated error metric when comparing joint angles with those calculated using an optoelectronic motion analysis system. Kinematic errors and error ranges [square brackets] are given. Error metrics with “r” represent the right side of the body only. Acronyms used include PSA, predefined sensor alignment; PA, proprietary algorithm; KF, Kalman filter; F/E, flexion/extension; P/S, Pronation/supination; IN/EX, internal/external rotation; EAD, Euler angle decomposition; FJM, functional joint movement; MFC, Magnetic field calibration; ABV, angle between vectors.

Study	Sample	Quality Score	Calibration	Sensor Fusion	Joint Angle Calculation	Task	Error Metric	Kinematic Errors
Study	Sample	Quality Score	Calibration	Sensor Fusion	Joint Angle Calculation	Task	Error Metric	F/E	P/S
[101]	n = 1	16	FJM	KF	Rotation matrix, least square filter	Eating routine	RMSE	21°	/
[101]	n = 1	16	FJM	KF	Rotation matrix, least square filter	Grooming routine	RMSE	7°	/
[30]	n = 1	16	PSA, static	Xsens KF	EAD	Elbow F/E and P/S	RMSE	[0.2°, 3.2°]	[0.2°, 3.2°]
[66]	n = 1	19	PSA	Xsens KF	EAD	Elbow flexion and P/S	Peak error	5.8°	24.1°
[66]	n = 1	19	PSA	Xsens KF	EAD	Water serving	Mean error	18.6°	11.7°
[61]	n = 4	15	PSA, static	Unscented KF	Forward kinematics	Arbitrary movement	RMSE	6.2°	13.0°
[67]	n = 8	16	Static	Unscented KF	Forward kinematics	Elbow F/E	RMSE	6.5°	/
[67]	n = 8	16	Static	Unscented KF	Forward kinematics	Elbow P/S	RMSE	/	5.5°
[94]	n = 1	16	PSA	Xsens KF	ABV	Elbow F/E	Mean error ± SD	−0.54° ± 2.63°	/
[94]	n = 1	16	PSA	Xsens KF	ABV	Elbow P/S	Mean error ± SD	/	−5.16° ± 4.5°
[95]	n = 1	18	PSA	InvenSense PA, MFC	EAD	Reaching	RMSE	7.9°	1.5°
[36]	n = 10	21	PSA, static, FJM	Xsens KF	EAD	Elbow F/E	RMSE ± SD	18.7° ± 2.7°	/
						Elbow P/S		/	15.8° ± 6.3°
						Rotating wheel		20.0° ± 3.7°	/
[92]	n = 12	20	FJM	KF	EAD	Miscellaneous	Proportional & Systematic error	0.00X +2.00°	−0.00Z −1.20°
[96]	n = 8	22	PSA, static	Gradient decent	EAD	Simulated front crawl	RMSE	15°	10°
[96]	n = 8	22	PSA, static	Gradient decent	EAD	Simulated breaststroke	RMSE	8°	6°
[82]	n = 3	9	/	Invensense PA	INMOCAP PA	Elbow F/E	%RMSE	2.44%	/
[75]	n = 1	18	Static, auto-calibration	Xsens KF	Kinematic constraint, EAD	Door opening	RMSE	2.7°	3.8°
[77]	n =1	13	Joint axis optimization	Xsens KF, MFC	Kinematic constraint, EAD	Pick-and-place,	Mean error ± SD	4.09° ± 3.43°	−5.16° ± 6.63°
[77]	n =1	13	Joint axis optimization	Xsens KF, MFC	Kinematic constraint, EAD	drinking	Mean error ± SD	4.09° ± 3.43°	−5.16° ± 6.63°
[111]	n = 15	18	FJM, static	YEI PA	EAD	Elbow F/E	RMSE	4°	/
[111]	n = 15	18	FJM, static	YEI PA	EAD	Elbow P/S	RMSE	/	4°
[68]	n = 6	19	PSA, static	Xsens KF	EAD	Mimic surgery	RMSE	8.2° ± 2.8°	/
[97]	n = 12	20	Static, FJM	Xsens KF	EAD	Box moving	RMSE	6.2°	12.2°
[69]	n = 14	16	PSA, static	iSen PA	iSen PA	Elbow F/E	RMSE	27.1°	/
[93]	n = 14	16	IMU caliper	Xsens KF	EAD	Elbow F/E	RMSE	1.9° ± 2.6°	/
[93]	n = 14	16	IMU caliper	Xsens KF	EAD	Elbow P/S	RMSE	/	2.9° ± 1.6
[41]	n = 10	21	Static, FJM, optimization	KF, TRIAD	EAD	Yoga sequence	RMSE	3°	3.3°
[70]	n = 6	14	Static	MFC, gradient decent	ABV	Simulated rowing	% Mean error ± SD r	2.19% ± 1.23%	/
[98]	n = 10	19	Static	Xsens KF	Xsens PA	Military movements	RMSE ± SD r	10.9° ± 5.3°	40.5° ± 27.6°
[99]	n = 5	19	Static	Perception Neuron PA	EAD	Box moving	RMSE	14.9°	14.3°
[108]	n = 10	18	Static, FJM	Xsens KF	Xsens PA	Gymnastics move	RMSE	4.2°	/
[78]	n = 10	10	Static	Madgwick filter	Euler angle	Walking	%RMSE (r)	5.80%	/
[113]	n = 1	21	Static, MFC, FJM	Madgwick filter	ABV	Elbow F/E	RMSE (r)	8.23°	/
						Elbow F/E with P/S		9.36°	/
						Walking		5.98°	/
						Simulated front crawl		5.6°	/
						Simulated rowing		6.53°	/
[71]	n = 10	18	Static	Xsens KF	Xsens PA	Box moving	RMSE (r)	28.2	/
						Box elevation		30.7	/
						Reaching at head height		34.2	/
[110]	n = 29	18	Static, functional	Xsens KF	Xsens PA	Tennis ball hitting	RMSE	1.5°	13.1°
[73]	/	10	Static	ADIS16448 PA	ABV	Rowing	Mean absolute error (r)	3.28°	/
[91]	n = 10	18	Static, functional	Orthogonalization, drift compensation	EAD	Yoga sequence	Mean absolute error	2°	4°
[83]	n = 1	17	Static	KF	Rotation about fixed axis	Elbow F/E	RMSE	3.82°	/
[83]	n = 1	17	Static	KF	Rotation about fixed axis	Elbow P/S	RMSE	/	3.46°
[84]	n = 1	21	Static	KF	EAD	Nordic walking	Mean error (r)	23.7°	/
[72]	n = 10	17	Static	Perception Neuron PA	/	Stationary walk	RMSE ± SD	3.4° ± 2.15°	/
						Distance walk		2.04° ± 1.48°	/
						Stationary jog		3.89° ± 2.96°	/
						Distance jog		1.92° ± 1.0°	/
						Stationary ball shot		2.81° ± 2.18°	/
						Moving ball shot		3.2° ± 1.75°	/
[52]	n = 2	20	Kinematic constraint, optimization	6D VQF	EAD	Pick-and-place, drinking	RMSE	2.1°	3.7°
[112]	n = 15	18	Static, FJM	Notch PA	Notch PA	Tennis hitting	RMSE	5.76°	6.66°
[74]	n = 15	17	Static pose	Notch PA	Notch PA	Elbow F/E	Mean error ± SD	17.55° ± 3.28°	/
						Hand-to-contralateral-shoulder		9.91° ± 3.18°	/
						Hand-to-top-of-head		3.34° ± 3.48°	/
[81]	n = 5	19	PSA, static	Mahony filter	Inverse kinematics	Fugl-Meyer task	RMSE	5.2° ± 2.1°	/
[106]	n = 10	19	Static, FJM	Unscented KF	EAD	Yoga sequence	RMSE	2.96° ± 0.95°	6.79° ± 2.31°
[88]	n = 7	20	Static	Perception Neuron PA	EAD	Flexion	RMSE	8.7°	/
						Extension		5.8°	/
						Pronation			7.2°
						Supination		/	7.8°
						Box lifting		12.5°	9.5°
[89]	n = 1	12	Regression modelling	gForcePro+ PA	ABV	Grasping	RMSE	3.4°	3.9°