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Background:Mild cognitive impairment (MCI) can be an early sign of Alzheimer’s disease and other types of dementia detectable through gait analysis. Curve walking, which demands greater cognitive and motor skills, may be more sensitive in MCI detection than straight walking. However, few studies have compared gait performance in older adults with and without MCI in these conditions. Objective:To compare the capability of curve and straight walking tests for the detection of MCI among older adults. Methods:We employed a Kinect v.2 camera to record the gait of 55 older adults (30 healthy controls, 25 with MCI) during single-task straight and curve walking tests. We examined 50 gait markers and conducted statistical analyses to compare groups and conditions. The trail was approved with protocol No. IR.SEMUMS.REC.1398.237 by the ethics committee of Semnan University of Medical Sciences in Iran. Results:Older adults with MCI exhibited more compromised gait performance, particularly during curve walking. Curve walking outperformed straight walking in MCI detection, with several gait markers showing significant differences between healthy controls and MCI patients. These markers encompass average velocity, cadence, temporal markers (e.g., gait cycle subphase durations), spatial markers (e.g., foot position changes during gait subphases), and spatiotemporal markers (e.g., step and stride velocities). Conclusions:Our study suggests curve walking as a more informative and challenging test for MCI detection among older adults, facilitating early diagnosis using non-invasive, cost-effective tools like the Kinect v.2 camera, complementing cognitive assessments in early diagnosis, and tracking MCI progression to dementia.
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Gait monitoring for older adults during guided walking: An integrated assistive robot and wearable sensor approach
Abstract An active lifestyle can mitigate physical decline and cognitive impairment in older adults. Regular walking exercises for older individuals result in enhanced balance and reduced risk of falling. In this article, we present a study on gait monitoring for older adults during walking using an integrated system encompassing an assistive robot and wearable sensors. The system fuses data from the robot onboard Red Green Blue plus Depth (RGB-D) sensor with inertial and pressure sensors embedded in shoe insoles, and estimates spatiotemporal gait parameters and dynamic margin of stability in real-time. Data collected with 24 participants at a community center reveal associations between gait parameters, physical performance (evaluated with the Short Physical Performance Battery), and cognitive ability (measured with the Montreal Cognitive Assessment). The results validate the feasibility of using such a portable system in out-of-the-lab conditions and will be helpful for designing future technology-enhanced exercise interventions to improve balance, mobility, and strength and potentially reduce falls in older adults.
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- PAR ID:
- 10387193
- Date Published:
- Journal Name:
- Wearable Technologies
- Volume:
- 3
- ISSN:
- 2631-7176
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Epidemiological studies link increased fall risk to obesity in older adults, but the mechanism through which obesity increases falls and fall risks is unknown. This study investigates if obesity (Body Mass Index: BMI>30 kg/m2) influenced gait and standing postural characteristics of community dwelling older adults leading to increased risk of falls. One hundred healthy older adults (age 74.0±7.6 years, range of 56-90 years) living independently in a community participated in this study. Participants' history of falls over the previous two years was recorded, with emphasis on frequency and characteristics of falls. Participants with at least two falls in the prior year were classified as fallers. Each individual was assessed for postural stability during quiet stance and gait stability during 10 meters walking. Fall risk parameters of postural sway (COP area, velocity, path-length) were measured utilizing a standard forceplate coupled with an accelerometer affixed at the sternum. Additionally, parameters of gait stability (walking velocity, double support time, and double support time variability) were assessed utilizing an accelerometer affixed at the participant's sternum. Gait and postural stability analyses indicate that obese older adults who fell have significantly altered gait pattern (longer double support time and greater variability) exhibiting a loss of automaticity in walking and, postural instability as compared to their counterparts (i.e., higher sway area and path length, and higher sway velocity) further increasing the risk of a fall given a perturbation. Body weight/BMI is a risk factor for falls in older adults as measured by gait and postural stability parameters.more » « less
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Dual-task tests can identify gait characteristics peculiar to fallers and nonfallers. Understanding the relationship between gait performance and dual-task related cognitive-motor interference is important for fall prevention. Dual-task adapted changes in gait instability/variability can adversely affect fall risks. Although implicated, it is unclear if healthy participants’ fall risks are modified by dual-task walking conditions. Seven healthy young and seven healthy older adults were randomly assigned to normal walking and dual-task walking sessions with a slip perturbation. In the dual-task session, the participants walked and simultaneously counted backwards from a randomly provided number. The results indicate that the gait changes in dual-task walking have no destabilizing effect on gait and slip responses in healthy individuals. We also found that, during dual-tasking, healthy individuals adopted cautious gait mode (CGM) strategy that is characterized by reduced walking speed, shorter step length, increased step width, and reduced heel contact velocity and is likely to be an adaptation to minimize attentional demand and decrease slip and fall risk during limited available attentional resources. Exploring interactions between gait variability and cognitive functions while walking may lead to designing appropriate fall interventions among healthy and patient population with fall risk.more » « less
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1017/wtc.2022.23
