Table 2.
Overview of technologies and data analysis methods.
| Category and technology used | Data analysis method | Author | |
| Strength | |||
|
|
Biodex System 2 multijoint testing | The highest peak torque measure, obtained during 4 repetitions, was recorded in Newton meters and used for data analysis. | Waltman et al [42] |
|
|
Biodex Medical System 3 | The highest peak torque value from the 3 repetitions was recorded for each speed. | Artese et al [31] |
|
|
Biodex Medical Systems 4 | Peak torque and mechanical work, normalized to body mass, were analyzed. | Bertoli et al [26] |
|
|
Biodex System 4 pro | The data were analyzed by averaging 3 trials of isometric and isokinetic strength (in Nm/kg). | Højvig et al [28] |
|
|
Digital inclinometer | Active and passive shoulder flexion/extension and external/internal rotation range of motion were measured with 3 trials averaged for data analysis. | Harrington et al [41]; Rao and Pattanshetty [27]; Ribeiro et al [34] |
|
|
Gravity inclinometer | The analysis assessed the prevalence of impaired shoulder range of motion, defined as an interlimb difference of 15 degrees or more between the affected and unaffected arms. Additionally, it evaluated the number of patients who experienced a decrease in shoulder ROMa greater than 15 degrees from their baseline measurements, indicating a significant loss of mobility after treatment or surgery. | De Groef et al [36,37] |
| Range of motion | |||
|
|
Kinect-based system | The study used a Kinect-based system to capture 3D motion data, extracting features like range of motion, hand height, elbow flexion, and movement acceleration. These were analyzed using machine learning algorithms to classify patients as having normal or impaired upper-body function. | Moreira et al [38] |
|
|
Automated motion analysis system using Microsoft Kinect | The Microsoft Kinect sensor was used to assess shoulder motion limitations. The technology tracked body landmarks and converted the captured data into joint angles using a custom algorithm. | Gritsenko et al [39] |
|
|
Microsoft Kinect Sensor | The Microsoft Kinect sensor captured participants' upper extremity motion trajectories during standardized seated arm movements. These data allowed for the reconstruction of each participant's reachable workspace envelope, divided into 4 quadrants relative to the shoulder joint. The reachable surface areas for each quadrant and the total workspace were calculated and then normalized by individual arm length to account for differences among participants. | Uhm et al [33] |
|
|
Force plate model 4060NC (Bertec Corp) and recorded through Motion Monitor Software (Innsport Training, Inc) | Balance was assessed using a force plate to measure postural sway in the medial-lateral and anterior-posterior planes under both static and dynamic conditions. For static balance evaluation, participants stood still for 30 seconds before and after moderate-intensity exercise. Dynamic balance was measured during the rising phase of an Instrumented Sit-to-Stand test, where participants quickly stood up from a seated position, and sway was recorded throughout this transition. | Wechsler et al [30] |
| Balance | |||
|
|
Balance plate (Bertec Corp) | Data collected from the CoPb included measurements of its location and displacement during standing trials, specifically focusing on the root mean squared excursion in the medial-lateral direction to evaluate postural stability and the risk of falling. | Monfort et al [35] |
|
|
Technobody-PK 200 WL, a computer-based dynamic balance platform | Participants performed the “Equilibrium Assessment” and “Sleight Assessment” tests on this device, which measured parameters such as anterior/posterior and medial/lateral sleight, balance assessments, number of targets reached, perimeter, and average pace. Each test was repeated 3 times, and the best score was recorded for analysis. | Zabi̇t Özdemi̇r and İyi̇gün [29] |
|
|
Computerized dynamic posturography with the SOT | Participants' sway responses were recorded under 6 sensory conditions that manipulate visual and somatosensory information. | Winters-Stone et al [40] |
|
|
NeuroCom SOTc | Equilibrium scores from the NeuroCom SOT under 6 conditions varying platform stability and visual input, with and without the serial sevens cognitive task, were analyzed to assess static balance and the impact of cognitive load. | Evans et al [32] |
aROM: range of motion.
bCoP: center of pressure.
cSOT: Sensory Organization Test.