Table 4 Features of Balance Analyses
From: Assessment of frailty: a survey of quantitative and clinical methods
| Â | Studies/parameters used to assess balance | Device | Clinical Test | Frailty Classification | Purpose |
|---|---|---|---|---|---|
1 | A. Chkeir et al. [10, 34] Rise Rate, Average Velocity of Trajectory Obtained From Reaction Force and CoP Trajectories | Balance Quality Testers (Bathroom Scales) | None | Frail and Non-Frail | Established the Relationship Among the Balance Parameter with the Fried Phenotype |
2 | Chang et al. [21] Balance | ePad and eReach | None | Pre-frail and Non-frail | Developed Frailty Model Using Artificial Neural Network. |
3 | A. Martinez-Ramirez et al. [69] Sway Area, Signal Patterns | Tri-Axial Inertial Sensor Unit | Quiet Standing Balance Test | Yes Pre-Classified According to the Fried phenotype | High Frequency Components Associated With Frailty Syndrome |
4 | G.M. Bertolotti et al. [35] Body Sway and Trunk Kinematics Data | Customized Inertial Sensor Unit (Gyro, and, Accelerometer) | Selected Tasks Performed from Tinetti Tests, Balance Evaluation Systems Test and Berg Balance | None | Validating the Use of Newly Developed Unit Against Balance Board and Marker-Based System. |
5 | Z. Lv et al. [40] CoM | Kinect | Double Leg Stance, sttar excursion balance Test | None | Validating Kinect V2 for Balance Measurement |
6 | A. Nalci et al. [79] Variation in pixel events | Camera | UPST | None | Developed Vision Based Model To Assess Balance |