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Dementia is a collective term for cognitive disorders primarily affecting memory, thinking, and reasoning. It is not a specific disease but a syndrome, with Alzheimer's disease being the most common cause, accounting for approximately 60-80% of cases. Other types include vascular dementia, Lewy body dementia, and frontotemporal dementia. Dementia affects millions worldwide, particularly older adults, though it is not a normal part of aging.
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Visualize a drone, with its propellers spinning rapidly, hovering mid-air. The fascinating movements and operations of this drone can be comprehended by applying the principle of general plane motion.
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In statistics, several tools are used to interpret the data. Measures of central tendency represent the characteristics of the data, such as mean, median, and mode. Additionally, measures of variance like standard deviation and range are used to find the spread of data from the mean. Relative standing measures the distance between data locations. Commonly used measures of relative standings are percentile, z score, and quartiles.
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A slider-crank mechanism converts rotational motion from the crank into linear motion of the slider or vice versa. This mechanism consists of three main parts: the crank, the connecting rod, and the slider. The movement of the slider-crank is an example of general plane motion as the fluctuating angle between the crank and the connecting rod. Consider a segment AB where point A is at the end of the slider and point B is on the diametrically opposite end to point A, on a crack. The variance in...
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Using Retinal Imaging to Study Dementia
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Sensor-based motion analysis for dementia detection: a systematic review.

Zongyi Jiang1, Maryam Ghahramani1,2, Nathan M D'Cunha3,4

  • 1Faculty of Science and Technology, University of Canberra, Canberra, ACT, Australia.

Frontiers in Digital Health
|January 30, 2026
PubMed
Summary
This summary is machine-generated.

Motion sensors show promise for early dementia detection by analyzing gait and daily activities. This review highlights sensor types, tasks, and methods for improved diagnosis, paving the way for more accurate and timely interventions.

Keywords:
dementiadiagnosismachine learningmotion analysissensor technologiesstatistical analysis

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Area of Science:

  • Biomedical Engineering
  • Neuroscience
  • Gerontology

Background:

  • Dementia diagnosis relies on subtle cognitive and motor changes.
  • Early detection is critical for effective management and care.
  • Sensor technology offers new avenues for continuous motion monitoring.

Purpose of the Study:

  • To systematically review motion-based dementia detection methods.
  • To analyze sensor types, placements, tasks, features, and analytical approaches.
  • To identify research gaps and guide future studies in motion assessment for dementia.

Main Methods:

  • Systematic review of literature from January 2015 to May 2025.
  • Searched PubMed, Web of Science, IEEE Xplore, and Scopus.
  • Included 23 articles focusing exclusively on motion-based dementia detection.

Main Results:

  • Various sensors (IMUs, pressure mats, cameras) and placements were used.
  • Motion tasks included gait, activities of daily living, and postural control.
  • Machine learning and statistical analyses were employed, showing motion features as sensitive dementia indicators.

Conclusions:

  • Motion-based assessments hold significant potential for dementia detection.
  • Standardization of methods is needed for improved reproducibility.
  • Future research should focus on large-scale data, multimodal integration, and explainable AI.