Activity recognition system for watching over infant children

Goto, Jun; Kidokoro, Takuya; Ogura, Tomohiro; Suzuki, Satoshi

doi:10.1109/roman.2013.6628549

Cited by 12 publications

(11 citation statements)

References 6 publications

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“…Children wore the sensor one full day (9 a.m.–4 p.m.) and performed a series of activities in a set order, each for 10 min to 2 h duration with some free-time light activities in between. Goto, 2013 [ 27 ] n = 10, 3–5 years old, sex not stated, clinical/TD not reported, recruited via childcare centre, Japan. To develop and evaluate a single arm sensor and SOM system to classify infant activities.…”

Section: Resultsmentioning

confidence: 99%

“…Most of the papers included an even number of male and female participants. The age range varied widely: eight papers included children under the age of 3 years, four papers included children aged between 3–5 years [ 26 , 27 , 33 , 34 ], and the remaining 12 papers included children over the age of 5 years or adults with a small set of children who fit the inclusion criteria. Some of these only included one participant fitting the inclusion criteria or were unclear in how many participants of each age were within the sample.…”

Section: Resultsmentioning

confidence: 99%

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Objective Measurement of Posture and Movement in Young Children Using Wearable Sensors and Customised Mathematical Approaches: A Systematic Review

Hendry,

Rohl,

Rasmussen

et al. 2023

Sensors

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Given the importance of young children’s postures and movements to health and development, robust objective measures are required to provide high-quality evidence. This study aimed to systematically review the available evidence for objective measurement of young (0–5 years) children’s posture and movement using machine learning and other algorithm methods on accelerometer data. From 1663 papers, a total of 20 papers reporting on 18 studies met the inclusion criteria. Papers were quality-assessed and data extracted and synthesised on sample, postures and movements identified, sensors used, model development, and accuracy. A common limitation of studies was a poor description of their sample data, yet over half scored adequate/good on their overall study design quality assessment. There was great diversity in all aspects examined, with evidence of increasing sophistication in approaches used over time. Model accuracy varied greatly, but for a range of postures and movements, models developed on a reasonable-sized (n > 25) sample were able to achieve an accuracy of >80%. Issues related to model development are discussed and implications for future research outlined. The current evidence suggests the rapidly developing field of machine learning has clear potential to enable the collection of high-quality evidence on the postures and movements of young children.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Objective Measurement of Posture and Movement in Young Children Using Wearable Sensors and Customised Mathematical Approaches: A Systematic Review

Hendry,

Rohl,

Rasmussen

et al. 2023

Sensors

View full text Add to dashboard Cite

show abstract

“…Moreover, it was simulated at two cases which the start position S and the target position G of the mass robot is different. In the 1st case it is assumed S 1 = [1, 1] G 1 = [13,9], and in the 2nd case assumes S 2 = [2, 9] G 2 = [7,3]. Indexes of S and G shows 1st case and 2nd case.…”

Section: Navigation Functionmentioning

confidence: 99%

“…4(A) : the start position and the target position is (1,1) and (13,9) and Fig. 4(B) : the start position and the target position is (2,9) and (7,3). Where the radius of the moving objects in M space is assumed to be 0.03.…”

Section: Navigation Functionmentioning

confidence: 99%

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Robot Navigation in dynamic environment for an indoor human monitoring

Iizuka

Nakamura

Suzuki

2014

The 23rd IEEE International Symposium on Robot and Human Interactive Communication

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This paper proposes a technique for navigation of a monitoring robot to watch over persons in a dynamic environment. In order to make an environmental map around the robot, localization of the robot and path finding to the target position are required so that the robot can move autonomously in the dynamic environment. In this study the position of robot and the environmental map are obtained by using Simultaneous Localization and Mapping (SLAM) which makes the map by using LRF with characteristic markers. Path finding to the target position is executed by using Navigation function that is a type of Artificial Potential Field (APF) method. Navigation function projects the work space and the obstacles to a topology space, and calculates value of APF. An effectiveness of the presented algorithm was confirmed since the point mass robot can reach the target position by avoiding moving objects through the simulation.

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Role of Multi-agent Systems in Health Care: A Review

Anubhuti¹,

Kaur²

2022

Emerging Technologies in Data Mining and Information Security

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Activity recognition system for watching over infant children

Cited by 12 publications

References 6 publications

Objective Measurement of Posture and Movement in Young Children Using Wearable Sensors and Customised Mathematical Approaches: A Systematic Review

Objective Measurement of Posture and Movement in Young Children Using Wearable Sensors and Customised Mathematical Approaches: A Systematic Review

Robot Navigation in dynamic environment for an indoor human monitoring

Role of Multi-agent Systems in Health Care: A Review

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