Table 2.

Key features of the studies.

Content and study			Purpose		Technology (number of sensors)		Placement location		Placement method		Measurement/methodology
Motion tracking
	Yu et al [27]	Monitor upper limb motion function of stroke patients		Accelerometer (n=2)		Forearm, upper arm		Straps		ROMa: Bobath’s handshake and shoulder touch
	Wang et al [24]	Monitor compensatory movements and evaluate their applicability in a clinical setting		9-DOFb IMUc (n=2)		Shoulder, torso		Zipped vest, Velcro straps		Compensatory movement of the shoulder girdle
	Li et al [18]	Evaluate upper limb motor function in hemiplegic patients		6-DOF IMU (n=2), EMGd (n=10)		Wrist, forearm, upper arm		Wristband, armband		Movements of major upper limb joints: shoulder, elbow, wrist, and finger joints
	Repnik et al [20]	Quantify upper limb movement for muscle activity analysis in stroke patients		9-DOF IMU (n=7), EMG (n=2)		Hand, wrist, forearm, upper arm, sternum		Wristband, armband, straps		Movement quantified: hand smoothness, trajectory, trunk stability, and muscle activity
	Tolvanen et al [23]	General motion tracking		Piezoresistive strain sensor (n=1)		Hand, wrist, forearm, upper arm (biceps, triceps)		Reusable adhesive layer		Opening-closing cycles (hand), muscle tension of the flexor sternum, biceps, upper arm, bicep curl, peck fly, and triceps
	Bai et al [13]	Monitor different body movements, muscle contraction, and relaxation		GYSe sensor		Upper arm, fingers		Direct winding		ROM: instant tensing, bending, static motions of fingers, varied contractions of the bicep
	Gu et al [15]	Identify hand motions, joint bending, hand posture, gesture, and sign language		Hydrogel-elastomer hybrid ionic sensor (n=10)		Hand, fingers		Water-borne adhesive		ROM: finger bending/extending and hand gestures
	Lee et al [17]	Analyze data from neurologically intact individuals and the free-living environment, and develop a system to monitor stroke survivors		Accelerometer (n=4)		Wrists, fingers		Rings, wristbands		General quantification of the amount of use of upper limb function
	Zhang P et al [26]	Monitor human movement with the use of a flexible resistance strain sensor with a porous structure		Strain sensor (n=1)		Upper arm, forearm, wrist, fingers		Velcro straps		ROM: finger wrist and elbow bending; responses to breathing
	Lee et al [16]	Facilitate the clinically fitted measurement of fine-motor finger and wrist joint movements. Characterize age-related changes in hand functions		9-DOF IMU (n=7)		Wrist, hand, fingers		Clip-on straps		ROM: finger movement (index finger, thumb flexion/extension) and wrist movement (ulnar/radial flexion)
	Zhang J et al [25]	Implement 3D motion velocity measurement, and propose a functional link artificial neural network model (FLANN)		Microthermal flow sensor (n=2)		Wrist		Straps		Trunk velocity, relative limb velocity, and absolute limb velocity
	Schwarz et al [21]	Evaluate spatiotemporal kinematic metrics for the assessment of upper limb movements after stroke		6-DOF IMU (n=8)		Sternum, shoulder, upper arm, forearm, hand, fingers, thumb		Medical tape/3D-printed flexible straps		ROM: shoulder, elbow, thumb, index flexion/extension, and wrist supination/pronation
	Formstone et al [14]	Develop a comprehensive system designed for the clinical environment, and quantify hand/wrist movement		9-DOF IMU (n=3), MMGf (n=2)		Sternum, upper arm, wrist, forearm		3D-printed housing cases attached with 3D-printed flexible resin straps		Shoulder twist angle (range), abduction, flexion, elbow twist angle, wrist flexion, and circumduction muscle activity
	Little et al [19]	Analyze kinematic and physiological features for predicting elbow motion intention		9-DOF IMU (n=3), EMG (n=4), stretch sensor (n=1)		Forearm, upper arm, torso		Straps, direct winding		Muscle activity, elbow flexion angle, and custom-made changes in muscle volume
	Schwerz de Lucena et al [22]	Real-time quantification of the effect of wearable feedback on hand counts for increasing hand activity		6-DOF IMU (n=1), magnetometer (n=4)		Wrist, fingers		Wristband, ring		“Hand counts”: finger flexion/extension, wrist flexion/extension, and wrist radial/ulnar deviation movement
Rehabilitation
	Ding et al [39]	Measure orientation and correct arm posture using vibrotactile actuators for stroke rehabilitation patients and therapists		9-DOF IMU (n=2)		Forearm, upper arm		Velcro straps		Body segment posture; forearm and upper arm orientation; trajectory of upper arm’s yaw, pitch, and roll; elbow angle; and forearm roll
	Kim et al [31]	Wearable upper limb motion tracking method for stroke rehabilitation therapy at home		6-DOF IMU (n=2)		Wrist, upper arm		Velcro straps		ROM: position and orientation of the wrist and elbow joints. Accuracy of motion estimation and motion matching
	Mohammadzadeh et al [34]	Develop and evaluate the feasibility of a wearable sensor-based motion-tracking system		6-DOF IMU (n=3)		Forearm, upper arm, sternum		Velcro straps		ROM: elbow joint angle
	Ploderer et al [35]	Patient monitoring system to support occupational therapists in upper limb rehabilitation work with stroke patients		9-DOF IMU (n=3)		Shoulder, upper arm, wrist		Velcro straps, medical tape		ROM of each degree of freedom
	Wang et al [28]	Evaluate garments equipped with sensors that support posture monitoring; used in upper extremity rehabilitation training of stroke patients		9-DOF IMU (n=3)		Scapula (shoulder blade), torso		Vest with Velcro straps		Analytical shoulder flexion, and analytical and functional elevation in the scapular plane
	Salchow-Hömmen et al [37]	Part of a feedback-controlled hand neuroprosthesis for the rehabilitation of patients who experience motor impairment of the hand		9-DOF IMU (n=16)		Hand, fingers, forearm		Skin-friendly tape		ROM: combined abduction and flexion motion
	Semjonova et al [38]	Evaluate the impact of the Double Aid (DAid) smart shirt; training process of patients with subacromial pain syndrome		Strain sensors (n=2)		Scapula		Commercial elastane-based fitness shirt		Perform exercise without moving the shoulders; detect movement or no movement of the shoulders
	Friedman et al [29]	Nonobtrusive option for monitoring wrist and hand movement; needed for stroke rehabilitation and other applications		Triaxial magnetometer (n=2), accelerometer (n=1)		Wrist, fingers		Watch-like enclosure, small neodymium ring worn on the index finger		Accuracy of monitoring finger motion, wrist flexion/extension, and wrist ulnar/radial deviation. Accuracy in estimating different levels of movement activity
	Kortier et al [32]	Ambulatory system using inertial sensors for hand kinematics, and evaluation of hand functioning		6-DOF IMU (n=15), 9-DOF IMU (n=6)		Hand, fingers, thumb		Double-sided adhesive tape/mounted on polyamide/elastane-fabricated glove		Static accuracy (ROM: flexion/extension, dynamic range, and repeatability)
	Kim et al [30]	Identify optimal sensor locations		Bending sensor (n=2)		Thumb, hand		Flexible fabric straps partially made of Lycra sewed on a glove structure		ROM; circumduction motion
	Liu et al [33]	Primary use of conductive stretchable fabrics to sense skin deformation during joint motion and infer the joint rotational angle		Strain sensor (n=2)		Forearm		Fabric		ROM: elbow flexion by various degrees; repeat motion at 3 levels of speed. Repeat each motion and perform free-form motions
	Pregnolato et al [36]	Define the clinical features of stroke patients while performing hand movements for rehabilitation training		9-DOF IMU (n=1), EMG (n=1)		Forearm		Armband		Detect the total muscle activity of the forearm circumference

^aROM: range of motion.

^bDOF: degrees of freedom.

^cIMU: inertial measurement unit.

^dEMG: electromyography.

^eGYS: graphene thin-film yarn sensor.

^fMMG: mechanomyography.