Mobile monitoring with wearable photoplethysmographic biosensors

Asada, H. Harry; Shaltis, P.; Reisner, Andrew; Rhee, Sokwoo; Hutchinson, Reginald C.

doi:10.1109/memb.2003.1213624

Cited by 401 publications

(228 citation statements)

References 57 publications

(44 reference statements)

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“…Therefore we concentrated on PPG and GSR signals for the analysis. PPG signal is a permanent signal 15 , which can be used to extract multiple parameters 13 like HR, SpO2, Respiration Rate etc. GSR signal is an induced signal, as certain derived feature responses directly correlates due to triggering of stressful events 15 .…”

Section: Physiological Signals Sensors and Experimental Setupmentioning

confidence: 99%

“…Certain clinically significant parameters like pulse, heart rate (HR) and heart rate variability (HRV) etc. have been successfully extracted by [13,20] from the morphology of the pulsatile component of PPG signal. These features were found by [18,27,28] , to be as reliable parameters, useful in mental health monitoring of a subject.…”

Section: Feature Extraction and Selectionmentioning

confidence: 99%

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Assessment of Driver Stress from Physiological Signals collected under Real-Time Semi-Urban Driving Scenarios

Singh¹,

Conjeti²,

Banerjee³

2014

IJCIS

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Designing a wearable driver assist system requires extraction of relevant features from physiological signals like galvanic skin response and photoplethysmogram collected from automotive drivers during real-time driving. In the discussed case, four stress-classes were identified using cascade forward neural network (CASFNN) which performed consistently with minimal intra-and inter-subject variability. Task-induced stress-trends were tracked using -based regression model with CASFNN configuration. The proposed framework will enable proactive initiation of rescue and relaxation procedures during accidents and emergencies.

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Section: Physiological Signals Sensors and Experimental Setupmentioning

confidence: 99%

Section: Feature Extraction and Selectionmentioning

confidence: 99%

Assessment of Driver Stress from Physiological Signals collected under Real-Time Semi-Urban Driving Scenarios

Singh¹,

Conjeti²,

Banerjee³

2014

IJCIS

View full text Add to dashboard Cite

show abstract

“…With people in industrialized nations living longer than ever before and an increase in average life expectancy of more than 25 years over the last century, the size of this group is set to increase, along with their demand on health care resources (Butler 1997). Identifying ways of monitoring this ageing population in their home environment is therefore very important, with one key example of the usefulness of this approach being the vulnerable periods during months of nontemperate weather.…”

Section: The Role Of Pervasive Sensing In Health Carementioning

confidence: 99%

From computers to ubiquitous computing by 2010: health care

Aziz

Pansiot

et al. 2008

Phil. Trans. R. Soc. A.

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Over the past decade, miniaturization and cost reduction in semiconductors have led to computers smaller in size than a pinhead with powerful processing abilities that are affordable enough to be disposable. Similar advances in wireless communication, sensor design and energy storage have meant that the concept of a truly pervasive ‘wireless sensor network’, used to monitor environments and objects within them, has become a reality. The need for a wireless sensor network designed specifically for human body monitoring has led to the development of wireless ‘body sensor network’ (BSN) platforms composed of tiny integrated microsensors with on-board processing and wireless data transfer capability. The ubiquitous computing abilities of BSNs offer the prospect of continuous monitoring of human health in any environment, be it home, hospital, outdoors or the workplace. This pervasive technology comes at a time when Western world health care costs have sharply risen, reflected by increasing expenditure on health care as a proportion of gross domestic product over the last 20 years. Drivers of this rise include an ageing post ‘baby boom’ population, higher incidence of chronic disease and the need for earlier diagnosis. This paper outlines the role of pervasive health care technologies in providing more efficient health care.

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“…[7][8][9][10] However, there are often several unique challenges to designing and implementing a system capable of monitoring physical activity without the use of large equipment. 10 As Corbishley and Rodriguez-Villegas 11 acknowledge, an ideal system must use small sensors, such that they do not interfere with the individual's movement pattern.…”

Section: Introductionmentioning

confidence: 99%

Accuracy and Precision of an Accelerometer-Based Smartphone App Designed to Monitor and Record Angular Movement over Time

Bittel

Elazzazi

Bittel

2016

Telemedicine and e-Health

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"Accuracy and precision of an accelerometer-based smartphone app designed to monitor and record angular movement over time. " Telemedicine and e-Health.22,4. 302-309. (2016 AbstractBackground: Therapeutic exercise is a central component in the management of many common conditions. It is imperative, therefore, that clinicians monitor and correct patient performance to facilitate the use of proper form both in the clinic and during home exercise programs. Although clinicians are trained to prescribe exercise and analyze form, there are many subtleties that may be missed by relying on visual assessment. This study investigated the accuracy and precision of a novel, exercise-training smartphone application (app), running on an iPhone Ò (Apple, Cupertino, CA) 4

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Mobile monitoring with wearable photoplethysmographic biosensors

Abstract: (MIT). He specializes in robotics, biomedical engineering, and system dynamics and control. His current research areas include wearable health monitoring, robotic aids for bedridden patients, vast DOF actuator systems, and multiphysics simulation. He received the B.

Cited by 401 publications

References 57 publications

Assessment of Driver Stress from Physiological Signals collected under Real-Time Semi-Urban Driving Scenarios

Assessment of Driver Stress from Physiological Signals collected under Real-Time Semi-Urban Driving Scenarios

From computers to ubiquitous computing by 2010: health care

Accuracy and Precision of an Accelerometer-Based Smartphone App Designed to Monitor and Record Angular Movement over Time

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