A wearable respiratory plethysmography using flexible sensor

Esfahani, Mohammad Iman Mokhlespour; Narimani, Roya; Ramezanzadehkoldeh, Masoud

doi:10.1504/ijbet.2013.055667

Cited by 10 publications

(4 citation statements)

References 16 publications

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“…By adding grapheme to the PVDF piezoelectric membrane, the sensibility of the chest strap at body temperature (37 °C) could be improved (Hernández-Rivera and Suaste-Gómez 2017). Based on distributed capacitance similar to the piezoelectric sensors, a new elastic displacement transducer could fulfill the wearable respiratory plethysmography besides RR monitoring (Mokhlespour Esfahani et al 2013). With a sheet of e-Textile fabric coated with piezo electric polymer, the underbody pressure distribution was delineated on the high-resolution pressure images.…”

Section: Piezoresistive and Piezoelectric Pressure Sensorsmentioning

confidence: 99%

Recent development of respiratory rate measurement technologies

et al. 2019

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Respiratory rate (RR) is an important physiological parameter whose abnormality has been regarded as an important indicator of serious illness. In order to make RR monitoring simple to perform, reliable and accurate, many different methods have been proposed for such automatic monitoring. According to the theory of respiratory rate extraction, methods are categorized into three modalities: extracting RR from other physiological signals, RR measurement based on respiratory movements, and RR measurement based on airflow. The merits and limitations of each method are highlighted and discussed. In addition, current works are summarized to suggest key directions for the development of future RR monitoring methodologies.

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Section: Piezoresistive and Piezoelectric Pressure Sensorsmentioning

confidence: 99%

Recent development of respiratory rate measurement technologies

et al. 2019

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“…Also, the capacitive transduction method is a novel technology that can be exploited for monitoring chests movements. In [17], a low-cost wearable respiratory system was developed to detect breathing activity using a flexible and stretchable capacitive sensor constituted by a bifilar helix of conductive wires sealed in an insulating tube and mounted on an elastic band applied on the user' chest. The obtained device showed high resolution, low cost, vibration-immunity and low power consumption.…”

Section: Introductionmentioning

confidence: 99%

An Overview of Wearable Piezoresistive and Inertial Sensors for Respiration Rate Monitoring

et al. 2021

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The demand for wearable devices to measure respiratory activity is constantly growing, finding applications in a wide range of scenarios (e.g., clinical environments and workplaces, outdoors for monitoring sports activities, etc.). Particularly, the respiration rate (RR) is a vital parameter since it indicates serious illness (e.g., pneumonia, emphysema, pulmonary embolism, etc.). Therefore, several solutions have been presented in the scientific literature and on the market to make RR monitoring simple, accurate, reliable and noninvasive. Among the different transduction methods, the piezoresistive and inertial ones satisfactorily meet the requirements for smart wearable devices since unobtrusive, lightweight and easy to integrate. Hence, this review paper focuses on innovative wearable devices, detection strategies and algorithms that exploit piezoresistive or inertial sensors to monitor the breathing parameters. At first, this paper presents a comprehensive overview of innovative piezoresistive wearable devices for measuring user’s respiratory variables. Later, a survey of novel piezoresistive textiles to develop wearable devices for detecting breathing movements is reported. Afterwards, the state-of-art about wearable devices to monitor the respiratory parameters, based on inertial sensors (i.e., accelerometers and gyroscopes), is presented for detecting dysfunctions or pathologies in a non-invasive and accurate way. In this field, several processing tools are employed to extract the respiratory parameters from inertial data; therefore, an overview of algorithms and methods to determine the respiratory rate from acceleration data is provided. Finally, comparative analysis for all the covered topics are reported, providing useful insights to develop the next generation of wearable sensors for monitoring respiratory parameters.

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“…The former type (e.g., video motion capture system) has been used mainly in laboratory environments, since sophisticated hardware or software is often needed. Wearable systems, though, are both portable and usable for diverse indoor and outdoor applications for ambulatory motion analysis; such applications include medical service systems (e.g., detection of falls or health problems), rehabilitation, ergonomics, and sport biomechanics [14,15,16,17,18,19,20,21,22,23,24,25,26]. Individuals being assessed for physical activity tend to prefer small, lightweight wearable devices that are easily operated and maintained, while also being compatible with daily activities [27,28,29].…”

Section: Introductionmentioning

confidence: 99%

Classifying Diverse Physical Activities Using “Smart Garments”

Esfahani

Nussbaum

2019

Sensors

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Physical activities can have important impacts on human health. For example, a physically active lifestyle, which is one of the most important goals for overall health promotion, can diminish the risk for a range of physical disorders, as well as reducing health-related expenditures. Thus, a long-term goal is to detect different physical activities, and an important initial step toward this goal is the ability to classify such activities. A recent and promising technology to discriminate among diverse physical activities is the smart textile system (STS), which is becoming increasingly accepted as a low-cost activity monitoring tool for health promotion. Accordingly, our primary aim was to assess the feasibility and accuracy of using a novel STS to classify physical activities. Eleven participants completed a lab-based experiment to evaluate the accuracy of an STS that featured a smart undershirt (SUS) and commercially available smart socks (SSs) in discriminating several basic postures (sitting, standing, and lying down), as well as diverse activities requiring participants to walk and run at different speeds. We trained three classification methods—K-nearest neighbor, linear discriminant analysis, and artificial neural network—using data from each smart garment separately and in combination. Overall classification performance (global accuracy) was ~98%, which suggests that the STS was effective for discriminating diverse physical activities. We conclude that, overall, smart garments represent a promising area of research and a potential alternative for discriminating a range of physical activities, which can have positive implications for health promotion.

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A wearable respiratory plethysmography using flexible sensor

Cited by 10 publications

References 16 publications

Recent development of respiratory rate measurement technologies

Recent development of respiratory rate measurement technologies

An Overview of Wearable Piezoresistive and Inertial Sensors for Respiration Rate Monitoring

Classifying Diverse Physical Activities Using “Smart Garments”

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