Detecting periodic limb movements in sleep using motion sensor embedded wearable band

Kye, Saewon; Moon, Junhyung; Lee, Tae‐Ho; Lee, Sangyeop; Lee, Kyoungwoo; Shin, Seung-Chul; Lee, Yong Seung

doi:10.1109/smc.2017.8122756

Cited by 16 publications

(12 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Due to the aging trend of the population of developed countries, these wearable technologies will allow different life situations of patients or elderly people to be monitored, specifically in terms of the vital signs that guarantee their health and well-being [16,17]. For example, these devices can measure a user's heart rate, blood pressure, respiratory function, and the level of calories burned during exercise and steps walked, among other aspects [18,19]. As Yetisen et al [13] state, medical data can be sent to a healthcare provider to receive therapeutic feedback or can act automatically by other devices in the network.…”

Section: Introductionmentioning

confidence: 99%

Empirical Study Based on the Perceptions of Patients and Relatives about the Acceptance of Wearable Devices to Improve Their Health and Prevent Possible Diseases

Guillén‐Gámez

Mayorga-Fernández

2019

Mobile Information Systems

View full text Add to dashboard Cite

In recent years, there has been a technological revolution affecting all areas of life, including health. Following this trend, a series of electronic devices called wearable technology have emerged with the aim of improving the quality of people’s life. These devices are made up of tools that help to prevent the development of chronic diseases and fight against the aging of society by monitoring the vital signs of users. Despite the advantages of using these devices from medical and health points of view, it is necessary to know the opinion of users regarding their use. For this reason, this study has been proposed. The purpose of this study is to analyse the perceptions of the subjects involved in the research regarding the acceptance of wearable devices, taking into account variables, such as age and gender. To this end, a nonexperimental, ex post facto design has been composed that combines descriptive and inferential techniques, with a sample of 606 patients and relatives belonging to a public health centre in the community of Madrid.

show abstract

Section: Introductionmentioning

confidence: 99%

Empirical Study Based on the Perceptions of Patients and Relatives about the Acceptance of Wearable Devices to Improve Their Health and Prevent Possible Diseases

Guillén‐Gámez

Mayorga-Fernández

2019

Mobile Information Systems

View full text Add to dashboard Cite

show abstract

“… Routine of children diagnosed with autistic spectral disorder and ADHD (attention deficit hyperactivity disorder) [ 20 , 21 ]. Estimating the severity of sleep related movement-disorders such as periodic limb movements (PLMs) [ 7 , 22 , 23 ]. Therapeutic rehabilitation of joint disabilities in war veterans [ 24 , 25 ].…”

Section: Actigraphymentioning

confidence: 99%

“…Estimating the severity of sleep related movement-disorders such as periodic limb movements (PLMs) [ 7 , 22 , 23 ].…”

Section: Actigraphymentioning

confidence: 99%

“…Some actigraphs tend to sample movement data too infrequently, thus leading to information loss in the output raw signal. Many prior studies have been conducted on short-duration actigraphy datasets and did not require extensive memory and computational resources for analysis [ 14 , 22 ]. Translating these studies into long-term activity monitoring solutions is not feasible unless the actigraphy data is subjected to significant compression and segmentation at the source.…”

Section: Actigraphymentioning

confidence: 99%

See 1 more Smart Citation

A Device-Independent Efficient Actigraphy Signal-Encoding System for Applications in Monitoring Daily Human Activities and Health

Athavale

Krishnan

2018

Sensors

View full text Add to dashboard Cite

Actigraphs for personalized health and fitness monitoring is a trending niche market and fit aptly in the Internet of Medical Things (IoMT) paradigm. Conventionally, actigraphy is acquired and digitized using standard low pass filtering and quantization techniques. High sampling frequencies and quantization resolution of various actigraphs can lead to memory leakage and unwanted battery usage. Our systematic investigation on different types of actigraphy signals yields that lower levels of quantization are sufficient for acquiring and storing vital movement information while ensuring an increase in SNR, higher space savings, and in faster time. The objective of this study is to propose a low-level signal encoding method which could improve data acquisition and storage in actigraphs, as well as enhance signal clarity for pattern classification. To further verify this study, we have used a machine learning approach which suggests that signal encoding also improves pattern recognition accuracy. Our experiments indicate that signal encoding at the source results in an increase in SNR (signal-to-noise ratio) by at least 50–90%, coupled with a bit rate reduction by 50–80%, and an overall space savings in the range of 68–92%, depending on the type of actigraph and application used in our study. Consistent improvements by lowering the quantization factor also indicates that a 3-bit encoding of actigraphy data retains most prominent movement information, and also results in an increase of the pattern recognition accuracy by at least 10%.

show abstract

“…Also it's helpful to collect data on a foot. [3] Smart Watches Tracking performance is becoming more popular also it's important for athletes to get health data during workouts. The wearable devices are key to making such measurements.…”

Section: Lifestyle and Healthcarementioning

confidence: 99%

A demand for wearable devices in health care

Vijayalakshmi¹,

Uma²,

Bhuvanya³

et al. 2018

IJET

View full text Add to dashboard Cite

With the popularity of wearable devices, along with the development of telecommunication system there is a need for obtaining the health and fitness outcomes. So the recent advances in data analysis techniques have opened up new possibilities for using wearable technology in the digital health ecosystem. In past, it's too difficult to use the wearable devices for healthcare system because of the size of those sensors. But now with front end amplification and wireless data transmission, the wearable devices are deployed in health monitoring systems. Although the devices are continuously monitoring the human's body activity and collect various physiological data to increase the quality of human's life. In this paper first we provide a research survey on available wearable or gadgets. Also we conclude with future directions in wearable research and market.

show abstract

Detecting periodic limb movements in sleep using motion sensor embedded wearable band

Cited by 16 publications

References 20 publications

Empirical Study Based on the Perceptions of Patients and Relatives about the Acceptance of Wearable Devices to Improve Their Health and Prevent Possible Diseases

Empirical Study Based on the Perceptions of Patients and Relatives about the Acceptance of Wearable Devices to Improve Their Health and Prevent Possible Diseases

A Device-Independent Efficient Actigraphy Signal-Encoding System for Applications in Monitoring Daily Human Activities and Health

A demand for wearable devices in health care

Contact Info

Product

Resources

About