Validation Of An Ear Worn Sensor For Activity Monitoring In COPD

Atallah, Louis; Zhang, JinFei; Lo, Benny; Shrikrishna, Dinesh; Kelly, Julia L.; Jackson, A D; Polkey, Michael I.; Yang, Guang‐Zhong; Hopkinson, Nicholas

doi:10.1164/ajrccm-conference.2010.181.1_meetingabstracts.a1211

Cited by 9 publications

(6 citation statements)

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“…Atallah et al [112] have developed an ear worn sensor that can be used to monitor activities and levels of exertion in patients with chronic obstructive pulmonary disease. Using sophisticated machine learning algorithms, the authors were able to identify several different types of physical activities and the intensity of those activities from a single ear worn sensor.…”

Section: Applicationsmentioning

confidence: 99%

“…One way to approach the problem of achieving early detection of exacerbation episodes is to detect changes in the level of activity performed by a patient [ 110 , 111 ] and assume that a decrease in activity level would be indicative of the likelihood of a worsening of the clinical status of the individual undergoing monitoring. Atallah et al [ 112 ] have developed an ear worn sensor that can be used to monitor activities and levels of exertion in patients with chronic obstructive pulmonary disease. Using sophisticated machine learning algorithms, the authors were able to identify several different types of physical activities and the intensity of those activities from a single ear worn sensor.…”

Section: Applicationsmentioning

confidence: 99%

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A review of wearable sensors and systems with application in rehabilitation

Patel

Park

Bonato

et al. 2012

J NeuroEngineering Rehabil

1,821

984

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The aim of this review paper is to summarize recent developments in the field of wearable sensors and systems that are relevant to the field of rehabilitation. The growing body of work focused on the application of wearable technology to monitor older adults and subjects with chronic conditions in the home and community settings justifies the emphasis of this review paper on summarizing clinical applications of wearable technology currently undergoing assessment rather than describing the development of new wearable sensors and systems. A short description of key enabling technologies (i.e. sensor technology, communication technology, and data analysis techniques) that have allowed researchers to implement wearable systems is followed by a detailed description of major areas of application of wearable technology. Applications described in this review paper include those that focus on health and wellness, safety, home rehabilitation, assessment of treatment efficacy, and early detection of disorders. The integration of wearable and ambient sensors is discussed in the context of achieving home monitoring of older adults and subjects with chronic conditions. Future work required to advance the field toward clinical deployment of wearable sensors and systems is discussed.

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Section: Applicationsmentioning

confidence: 99%

Section: Applicationsmentioning

confidence: 99%

A review of wearable sensors and systems with application in rehabilitation

Patel

Park

Bonato

et al. 2012

J NeuroEngineering Rehabil

1,821

984

View full text Add to dashboard Cite

show abstract

“…Despite these challenges, compelling progress continues to be made across disciplines. For example, efforts in computer science have used machine learning algorithms to measure levels of exertion in patients with chronic obstructive pulmonary disease using the data from a single ear-worn sensor [48]. Unfortunately, the application of machine learning models such as in the previous example occurs far too infrequently relative to the number of available algorithms.…”

Section: Lack Of Standardization and Collaborationmentioning

confidence: 99%

Digital Endpoints: Definition, Benefits, and Current Barriers in Accelerating Development and Adoption

Landers¹,

Dorsey²,

Saria³

2021

Digit Biomark

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The assessment of health and disease requires a set of criteria to define health status and progression. These health measures are referred to as “endpoints.” A “digital endpoint” is defined by its use of sensor-generated data often collected outside of a clinical setting such as in a patient’s free-living environment. Applicable sensors exist in an array of devices and can be applied in a diverse set of contexts. For example, a smartphone’s microphone might be used to diagnose or predict mild cognitive impairment due to Alzheimer’s disease or a wrist-worn activity monitor (such as those found in smartwatches) may be used to measure a drug’s effect on the nocturnal activity of patients with sickle cell disease. Digital endpoints are generating considerable excitement because they permit a more authentic assessment of the patient’s experience, reveal formerly untold realities of disease burden, and can cut drug discovery costs in half. However, before these benefits can be realized, effort must be applied not only to the technical creation of digital endpoints but also to the environment that allows for their development and application. The future of digital endpoints rests on meaningful interdisciplinary collaboration, sufficient evidence that digital endpoints can realize their promise, and the development of an ecosystem in which the vast quantities of data that digital endpoints generate can be analyzed. The fundamental nature of health care is changing. With coronavirus disease 2019 serving as a catalyst, there has been a rapid expansion of home care models, telehealth, and remote patient monitoring. The increasing adoption of these health-care innovations will expedite the requirement for a digital characterization of clinical status as current assessment tools often rely upon direct interaction with patients and thus are not fit for purpose to be administered remotely. With the ubiquity of relatively inexpensive sensors, digital endpoints are positioned to drive this consequential change. It is therefore not surprising that regulators, physicians, researchers, and consultants have each offered their assessment of these novel tools. However, as we further describe later, the broad adoption of digital endpoints will require a cooperative effort. In this article, we present an analysis of the current state of digital endpoints. We also attempt to unify the perspectives of the parties involved in the development and deployment of these tools. We conclude with an interdependent list of challenges that must be collaboratively addressed before these endpoints are widely adopted.

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“…39 Ear-worn activity sensors have been used to provide early detection of the decreases in activity levels that may be associated with exacerbations of COPD. 40 Biochemical sensors were tested by Ahn 41 for estimating blood gas concentration. Garments that integrate sensing capabilities have allowed for embedding of sensors to collect electrocardiographic and electromyographic data.…”

Section: Remote Monitoringmentioning

confidence: 99%

Rural and remote care

Goodridge

Marciniuk

2016

Chron Respir Dis

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The challenges of providing quality respiratory care to persons living in rural or remote communities can be daunting. These populations are often vulnerable in terms of both health status and access to care, highlighting the need for innovation in service delivery. The rapidly expanding options available using telehealthcare technologies have the capacity to allow patients in rural and remote communities to connect with providers at distant sites and to facilitate the provision of diagnostic, monitoring, and therapeutic services. Successful implementation of telehealthcare programs in rural and remote settings is, however, contingent upon accounting for key technical, organizational, social, and legal considerations at the individual, community, and system levels. This review article discusses five types of telehealthcare delivery that can facilitate respiratory care for residents of rural or remote communities: remote monitoring (including wearable and ambient systems; remote consultations (between providers and between patients and providers), remote pulmonary rehabilitation, telepharmacy, and remote sleep monitoring. Current and future challenges related to telehealthcare are discussed.

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Validation Of An Ear Worn Sensor For Activity Monitoring In COPD

Cited by 9 publications

References 0 publications

A review of wearable sensors and systems with application in rehabilitation

A review of wearable sensors and systems with application in rehabilitation

Digital Endpoints: Definition, Benefits, and Current Barriers in Accelerating Development and Adoption

Rural and remote care

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