Conventional video-based system for measuring the subtask speed of the Timed Up and Go Test in older adults: Validity and reliability study.

The Timed Up and Go Test (TUG) is a simple fall risk screening test that covers basic functional movement; thus, quantifying the subtask movement ability may provide a clinical utility. The video-based system allows individual's movement characteristics assessment. This study aimed to investigate the concurrent validity and test-retest reliability of the video-based system for assessing the movement speed of TUG subtasks among older adults. Twenty older adults participated in the validity study, whilst ten older adults participated in the reliability study. Participant's movement speed in each subtask of the TUG under comfortable and fast speed conditions over two sessions was measured. Pearson correlation coefficient was used to identify the validity of the video-based system compared to the motion analysis system. Intraclass correlation coefficient (ICC3,2) was used to determine the reliability of the video-based system. The Bland-Altman plots were used to quantify the agreement between the two measurement systems and two repeatable sessions. The validity analysis demonstrated a moderate to very high relationship in all TUG subtask movement speeds between the two systems under the comfortable speed (r = 0.672-0.906, p < 0.05) and a moderate to high relationship under the fast speed (r = 0.681-0.876, p < 0.05). The reliability of the video-based system was good to excellent for all subtask movement speeds in both the comfortable speed (ICCs = 0.851-0.967, p < 0.05) and fast speed (ICCs = 0.720-0.979, p < 0.05). The Bland-Altman analyses showed that almost all mean differences of the subtask speed of the TUG were close to zero, within 95% limits of agreement, and symmetrical distribution of scatter plots. The video-based system was a valid and reliable tool that may be useful in measuring the subtask movement speed of TUG among healthy older adults.

Variability of gait characteristics in lameness elephant.

Lameness has a significant impact not only on the economy but also on elephant welfare. Several gait characteristics are altered to compensate for the discomfort. The traditional approach to detecting lameness has relied on mahout and veterinarian observation. The study aimed to determine how lameness affected the variability of an elephant's gait by using a three-dimensional inertial measurement unit (IMU) with Wi-Fi sensors. Five elephants with lameness, as determined by an experienced veterinarian and two, non-lamed elephants, aged between 58-80 years were included in the study. Gait biomechanics including limb segment motion, obtained from individually gyrometric- and accelero-based parameters and demonstrated as a graphical pattern showing changes in absolute rotation angle over time. The result revealed some character changes in gait kinematics parameters, but it was heterogeneity with an inconclusive pattern. The interlimb coordination could be a part of maintaining the actual locomotion pattern, or it could be a result of the mild degree of lameness for which all of the clients have compensated. This study introduces a new objective method for quantifying gait changes caused by lameness, additional research is required to make this objective more clinically applicable.

Three-Day Remote Monitoring of Gait Among Young and Older Adults Using Participants' Personal Smartphones.

Conventional one-time gait analyses do not evaluate walking across more than a few steps, cannot monitor changes longitudinally, and do not reflect performance in real-life environments. To successfully quantify age-related gait decrement, technology that can continuously monitor gait is vital. This study examined the feasibility and validity for participant smartphones to remotely assess gait. In addition, the authors investigated whether smartphone-derived measures could differentiate between young and older adults (fallers and nonfallers). A total of 63 adults completed clinical and gait assessment in the laboratory and donned their smartphones for 3 days in the real-life environment. A custom-built Android application collected triaxial accelerations with spatiotemporal gait measures computed and compared between groups. Across 11 brands and 10 Android versions, smartphone-derived gait parameters were valid. Furthermore, results indicated age-related differences in walking during the 3-day assessment. However, no disparities were found between older adult groups. Smartphone-based evaluations may improve real-life screening of adults with gait deficits.

Smartphone-Based Assessment of Gait During Straight Walking, Turning, and Walking Speed Modulation in Laboratory and Free-Living Environments.

As turns and walking speed modulation are crucial for functional mobility, development of a field-based tool to objectively evaluate non-steady-state gait is essential. This study aimed to quantify spatiotemporal gait using three Android smartphones during steady-state walking, turns, and gait speed modulation in laboratory and free-living environments. In total, 24 adults ambulated along a 10-m walkway in both environments under seven conditions: straight walking, 90° left or right turn, and modulating gait speed from usual-slow, usual-fast, slow-fast, and fast-slow. Two smartphones were attached to the body, with another phone placed in a shoulder bag. Gait velocity, step time, step length, cadence, and symmetry were computed from smartphone-based tri-axial accelerometers and validated with motion capture and video, in laboratory and free-living environments, respectively. Validity was assessed using Pearson's correlation and Bland-Altman analysis. Gait velocity results revealed moderate to very high validity across all walking conditions, smartphone models, smartphone locations, and environments. Correlations for gait velocity ranged between 0.87-0.91 and 0.79-0.83 for straight walking, 0.86-0.95 and 0.86-0.89 for turning, and 0.51-0.90 and 0.67-0.89 for speed modulation trials, in laboratory and free-living environments, respectively. Step time, step length, and cadence demonstrated high to very high correlations for straight walking and turns. However, symmetry results revealed high correlations only during straight walking in the laboratory. Conditions that included slow walking showed negligible to moderate validity with a high bias. In conclusion, smartphones can be employed as field-based devices to assess steady-state walking, turning, and speed modulation across environment, model, and placement when walking faster than 0.5 m/s.

Cognitive and visual demands, but not gross motor demand, of concurrent smartphone use affect laboratory and free-living gait among young and older adults.

BACKGROUND: As smartphones are an integral part of daily activities, understanding the underlying mechanism associated with concurrent cell phone use while walking may help reduce the risks of injury. RESEARCH QUESTION: This study examined the effect of cognitive, visual, and gross motor demands while using a phone during gait among young and older adults in the laboratory and free-living environments. METHODS: Twelve young and twelve older adults walked along a 10-m walkway under five conditions: single-task walking (Walk), walking and bi-manually holding a phone (Walk-Hold), walking while looking at a phone held in front of the participants (Walk-Look), walking while answering questions (Walk-Answer), and walking while texting (Walk-Text). All conditions were performed in laboratory and free-living environments. Gait velocity, step time, step length, and cadence were obtained using a smartphone with a built-in accelerometer attached to the body. The dual-task cost (DTC) was also assessed. A three-way ANOVA was utilized for all parameters. RESULTS: While no three-way interactions were found for any parameter, group × condition interactions were significant for gait velocity, step time, step length, cadence and their corresponding DTC. Decreased gait velocity, step length and cadence, with increased step time was demonstrated during Walk-Look, Walk-Answer, and Walk-Text, compared to Walk and Walk-Hold. While older adults markedly changed their gait during Walk-Answer and Walk-Text, these changes were less pronounced among young adults. SIGNIFICANCE: Visual and cognitive demand while concurrently using a phone influenced gait, especially among the elderly. Environment did not accentuate gait alterations during concurrent phone use. Therefore, smartphone technology should be developed to detect dual-task walking and temporarily modify functionality to reduce risk of injury from divided attention.