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Dementia Patient's Behavior Evaluation Using Noninvasive Ambient Sensor

Dementia Patient's Behavior Evaluation Using Noninvasive Ambient Sensor

Status
UNKNOWN
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT03120741
Enrollment
35
Registered
2017-04-19
Start date
2017-05-31
Completion date
2018-08-31
Last updated
2017-04-19

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Mild Cognitive Impairment, Dementia

Keywords

Healthcare Quality

Brief summary

This study is an observational study that uses daily activity and environmental sensing techniques to establish behavioral models of early dementia patients and cognitive healthy function to assess their daily behavior and determine their activities. Specifically, the team will collect information on a number of wireless sensors for dementia, mild cognitive impairment and healthy elderly residents, and use special mathematical models to establish the behavior of the two groups of subjects Model. The model will be developed a reliable algorithm to assess health risk of the subjects.

Detailed description

With the help of intelligent home environment and Pervasive Computing, it is possible to bring information about the behavior of the patients to the caregivers and their relatives. In this study, non-invasive wireless sensors such as infrared motion sensor the switch sensor will be built in the home of the subjects. The wireless sensor data collected by the input to the team's activity identification system in order to assess the mathematical model of the subjects capacity and immediate judgment of their activities. In the identification of activities can be divided into two categories of behavior, risk behavior (harmful to the subjects) and protective behavior (beneficial to the subjects), real-time activity detection, can avoid dangerous behavior, such as water and gas off, roaming , Repetitive behavior (over-eating), forgetting to eat and day-night reversal (sleep disturbance), etc., the protection of behavior can be observed through a long time to help patients conduct beneficial behavior, such as regular quantitative diet.

Interventions

None listed

Sponsors

National Taiwan University Hospital
Lead SponsorOTHER

Study design

Observational model
CASE_CONTROL
Time perspective
OTHER

Eligibility

Sex/Gender
ALL
Age
65 Years to 100 Years
Healthy volunteers
Yes

Inclusion criteria

* Can communicate in Mandarin or Taiwanese. * Consciousness is clear. * Can do the daily activity by their own.

Exclusion criteria

* Have a serious cardiopulmonary disease or physical activity is limited to those unable to carry out daily activities. * Consciousness is not clear. * Difficult communication, such as: aphasia patients, the use of respirator patients. * Suffering from serious mental illness that can not match. * Adopt absolute isolation, such as: open tuberculosis patients. * Hearing or severe visual impairment that can not match. * Can not exercise their consent.

Design outcomes

Primary

MeasureTime frameDescription
The relationship between moving pattern change and dementia.6 monthsMotion sensors will be installed on the ceiling. We will analyze multiple sensors to see how the participant move from one location to another. The data whether the participant is wandering or not and times of wandering will be measured.
The relationship between daily routine change and dementia.6 monthsMotion sensors, switch sensors, and current sensors will be installed in the home of the participant. The room which the participant is in, the appliance which the participant is using will be measured.
The relationship between sleeping time change and dementia.6 monthsMotion sensors will be installed in the bed or on the ceiling. The time when the participant goes to sleep, and the times the participant turns over during sleep will be measured.

Countries

Taiwan

Contacts

Primary ContactLi-Chen Fu, Doctor
lichen@ntu.edu.tw+886-2-3366-4888

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026