mHealth Sensors, Techniques, and Applications for Managing Wandering Behavior of People with Dementia: A Review

Vuong, Nhu Khue; Chan, Syin; Lau, Chiew Tong

doi:10.1007/978-3-319-12817-7_2

Cited by 15 publications

(11 citation statements)

References 61 publications

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“…Using the above derived relationship, for a room of size 10 m × 10 m, minimum standard deviation should occur when the length of each region is 3.33 m, or all regions have the same area, 3.33 m × 10 m. This situation is possible when the length of the actual LED light beam with the room edge effect is 8.33 m or the beam radius is 4.17 m. This is the same value as obtained from the plot between beam radius and average error from the simulation results as shown in Figure 9 (Case I). In addition, using (24), the minimum standard deviation value obtained is 3.04 m, which is same as the value obtained from the simulation. Based on the intuition and the results obtained from two rectangular LED beams, a generalised scenario is considered where an array of m × n LEDs is installed in a room with length h g and breadth b g .…”

Section: Multiple Led Indoor Positioning Systemsupporting

confidence: 63%

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Optical Wireless Communication Based Indoor Positioning Algorithms: Performance Optimisation and Mathematical Modelling

Ajmani¹,

Sinanović²,

Boutaleb³

2018

Computation

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In this paper, the performance of the optimal beam radius indoor positioning (OBRIP) and two-receiver indoor positioning (TRIP) algorithms are analysed by varying system parameters in the presence of an indoor optical wireless channel modelled in line of sight configuration. From all the conducted simulations, the minimum average error value obtained for TRIP is 0.61 m against 0.81 m obtained for OBRIP for room dimensions of 10 m × 10 m × 3 m. In addition, for each simulated condition, TRIP, which uses two receivers, outperforms OBRIP and reduces position estimation error up to 30%. To get a better understanding of error in position estimation for different combinations of beam radius and separation between light emitting diodes, the 90th percentile error is determined using a cumulative distribution frequency (CDF) plot, which gives an error value of 0.94 m for TRIP as compared to 1.20 m obtained for OBRIP. Both algorithms also prove to be robust towards change in receiver tilting angle, thus providing flexibility in the selection of the parameters to adapt to any indoor environment. In addition, in this paper, a mathematical model based on the concept of raw moments is used to confirm the findings of the simulation results for the proposed algorithms. Using this mathematical model, closed-form expressions are derived for standard deviation of uniformly distributed points in an optical wireless communication based indoor positioning system with circular and rectangular beam shapes.

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Section: Multiple Led Indoor Positioning Systemsupporting

confidence: 63%

“…Dementia is an ongoing illness which causes disorientation [22,23] and is a serious concern for caregivers as the people with dementia may get lost and walk into dangerous situations or places. This is one of the reasons that position tracking systems can be employed to improve their care [24,25].…”

Section: Introductionmentioning

confidence: 99%

Optical Wireless Communication Based Indoor Positioning Algorithms: Performance Optimisation and Mathematical Modelling

Ajmani¹,

Sinanović²,

Boutaleb³

2018

Computation

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“…This setting is even more complex to be used for trucking patients. Actually most of the other studies and systems that we found in the literature are designed for monitoring dementia patient for indoor activities [5,6,7]. These technologies are very complex to be used for monitor the outdoor patients activities.…”

Section: Related Research Workmentioning

confidence: 99%

Developing an Android App for Dementia Patient Location: Prevention of Wandering Case Study

Alraddadi¹,

Fiaidhi

Mohammed

2017

IJBSBT

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“…A lot of research has revealed that the frequent wanders are more vulnerable to experience adverse events, such as falling, elopement, boundary transgression and getting lost [4] [5]. Wandering manifests itself as aimless movement, repetitive locomotion with no identifiable goal and disorientation to time and place [6] [7]. Thus, managing wandering behavior of people with dementia has become increasingly imperative due to its high prevalence, negative outcomes and burden on caregivers [8].…”

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confidence: 99%

Detecting Dementia-Related Wandering Locomotion of Elders by Leveraging Active Infrared Sensors

Lin¹,

Zhao²,

Wang³

2018

JCC

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For elders with dementia, wandering is among the most problematic, frequent and dangerous behavior. Managing wandering behavior has become increasingly imperative due to its high prevalence, negative outcomes and burden on caregivers. We study to propose an active infrared-based method to identify wandering locomotion by monitoring rhythmical repetition of an elder's indoor motion events. Specifically, we utilize our customized active infrared sensors to collect human indoor motions that will be converted into motion events by using hardware redundancy technique. Each motion event is a directed motion obtained via introducing temporal and dimensions into the spatial motion data. Based on the most cited spatial-temporal patterns of wandering locomotion, a spatiotemporal model is then proposed to identify wandering locomotion from an ongoing sequence of motion events. Experimental evaluation on eight individuals' real-world motion datasets has shown that our proposed method is able to effectively identify wandering locomotion from repetitive events collected from active infrared sensors with a value over 98% for both accuracy and precision based on properly chosen parameters. Wandering in elders with dementia that follow specific spatiotemporal patterns can be reliably identified by analyzing repetitive motion events collected from active infrared sensors based on the well-known spatiotemporal patterns of wandering locomotion.

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mHealth Sensors, Techniques, and Applications for Managing Wandering Behavior of People with Dementia: A Review

Cited by 15 publications

References 61 publications

Optical Wireless Communication Based Indoor Positioning Algorithms: Performance Optimisation and Mathematical Modelling

Optical Wireless Communication Based Indoor Positioning Algorithms: Performance Optimisation and Mathematical Modelling

Developing an Android App for Dementia Patient Location: Prevention of Wandering Case Study

Detecting Dementia-Related Wandering Locomotion of Elders by Leveraging Active Infrared Sensors

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