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Background: The type of foam pad used in the modified Clinical Test of Sensory Interaction and Balance (mCTSIB) influences the accuracy with which elderly fallers are identified. Two types of foam are commonly used in practice: Airex and Neurocom foam.

Objective: The aim of this study was to assess the accuracy with which elderly fallers can be identified when the Airex foam and Neurocom foam are used in the mCTSIB.

Methods: One hundred eighty-four elderly participants with a mean age of 69 years were classified into faller and nonfaller groups based on their 12-month fall history. Balance stability was measured under four conditions of the mCTSIB for 120 s each: standing on a floor or a foam pad with their eyes open or eyes closed. The time needed to maintain stability was measured by a stopwatch, and postural sway characteristics were measured using an acceleration-based system. Comparisons between groups were performed by two-way mixed ANOVA. The accuracy of differentiating elderly fallers from nonfallers with different foam types was evaluated using receiver operating characteristic curve (ROC) analysis. The time to maintain stability under four conditions of the mCTSIB (composite score) and under two conditions on the foam (foam score) were used for the ROC analysis.

Results: The results showed that the nonfallers required more time to maintain stability and had a smaller sway area than the fallers ($p<0.001$). The foam led to a larger difference between groups, suggesting the use of foam in examining the risk of falls. The Airex and the Neurocom foam pads led to a large area under the curve (0.93 to 0.95) in identifying elderly fallers and nonfallers when the composite and foam scores were used. A cutoff score of 447/480 s for the composite score and 223/240 s for the foam score yielded a posttest accuracy of 88% to 89%, with a sensitivity of 0.80–0.92 and specificity of 0.88–0.95.

Conclusion: In conclusion, Airex and Neurocom foam can be used interchangeably with guidance in the mCTSIB, as they led to the accurate identification of elderly fallers among older persons who could walk and live independently in the community.

Instrumented gait analysis allows for the identification of walking parameters to predict cognitive decline and the worsening of dementia. The aim of this study was to perform a meta-analysis to better clarify which gait parameters are affected or modified with the progression of the dementia in a larger sample, as well as which gait assessment conditions (single-task or dual-task conditions) would be more sensitive to reflect the influence of dementia. Literature searches were conducted with the keywords “quantitative gait” OR “gait analysis” AND “dementia” AND “single-task” AND “dual-task,” and for “quantitative gait” OR “gait analysis” AND “dementia” AND “fall risk” on PubMed, EMBASE, the Cochrane Library, Scopus, and Web of Science. The results were used to perform a systematic review focussing on instrumental quantitative assessment of the walking of patients with dementia, during both single and dual tasks. The search was performed independently by two authors (C. R. and C. M.) from January 2018 to April 2020 using the PICOS criteria. Nine publications met the inclusion criteria and were included in the systematic review. Our meta-analysis showed that during a single task, most of the spatiotemporal parameters of gait discriminated best between patients with dementia and healthy controls, including speed, cadence, stride length, stride time, stride time variability, and stance time. In dual tasks, only speed, stride length, and stride time variability discriminated between the two groups. In addition, compared with spatial parameters (e.g. stride length), some temporal gait parameters were more correlated to the risk of falls during the comfortable walking in a single task, such as cadence, stride time, stride time variability, and stance time. During a dual task, only the variability of stride time was associated with the risk of falls.

This narrative review examines the use of inertial measurement units (IMUs) for assessing gait balance control. Impaired gait balance control is associated with an increased risk of falls and reduced mobility, particularly in older adults. Traditional methods of assessing gait balance control, such as clinical balance assessments and camera-based motion analysis, have limitations in terms of reliability, cost, and practicality. Wearable sensor technology, including IMUs, offers a more accessible and cost-effective alternative for assessing gait and balance performance in real-world settings. IMUs, equipped with tri-axial accelerometers, gyroscopes, and magnetometers, can directly measure body movement and provide quantifiable data. This review explores the advantages and limitations of using IMUs for assessing gait balance control, including the measurement of anticipatory postural adjustments (APAs) for gait initiation, spatiotemporal gait parameters, center of mass (COM) motion during walking, and data-driven machine learning models. IMUs have shown promise in quantifying APAs, estimating gait spatiotemporal parameters, assessing COM motion, and using machine learning algorithms to classify and predict balance-related outcomes. However, further research is needed to establish standardized protocols, validate IMU-based measurements, and determine the specific IMU parameters that correlate with balance control ability. Overall, IMUs have the potential to be a valuable tool for assessing gait balance control, monitoring changes over time, and tracking interventions to improve balance control in both clinical and research settings.

Elbow joint loading was evaluated during a forward fall at various elbow initial flexion angles, in order to determine which is the best elbow initial flexion angles to prevent the elbow injury during a fall. Subjects were asked to perform a forward fall and followed by a push-up motion in different elbow initial flexion angles: 0°, 20°, 40° and unrestricted group. Fall on the outstretched hand is the leading cause of upper extremity injury. There are far more extension type of supra-condylar fracture of the elbow than flexion type. Flexion of the elbow may represent the effects of damper and spring. Using the motion analysis system, the kinematics and kinetics of the elbow joint were investigated under various elbow initial flexion angles. The loading biomechanics of the elbow joint differed with various elbow initial flexion angles. The ground reaction forces decrease with increase of elbow flexion upon impact. Different initial elbow flexion angles would affect the biomechanics of upper extremities during falls. Forward fall with elbow in extension is more dangerous. Knowledge of elbow kinematics and kinetics may be helpful in preventing injuries by reducing the ground reaction force with changes of the elbow initial flexion angles during a fall.