Sleep apnea detection using features from the respiration and the ecg recorded with smart-shirts

Mirmohamadsadeghi, Leila; Fallet, Sibylle; Buttu, Andréa; Saugy, Jonas; Rupp, Thomas; Heinzer, Raphaël; Vesin, Jean‐Marc; Millet, Grégoire P.

doi:10.1109/biocas.2014.6981645

Cited by 8 publications

(5 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In patients with COPD, bioimpedance measurements were combined with electromyography and mechanomyography measurements assessing muscle activity [ 53 ], showing the applicability of noninvasive multimodal respiratory assessment. Regarding sleep apnea, recent work evaluated a shirt with ECG and bioimpedance for monitoring in healthy volunteers [ 54 ]. In addition, in patients with sleep apnea, a wearable bioimpedance device was able to detect apnea events, which opens opportunities for unobtrusive screening, diagnostics, and treatment monitoring in sleep apnea [ 49 ].…”

Section: Application Areas Of Bioimpedance Monitoring For Chronic Con...mentioning

confidence: 99%

“…Interestingly, studies have indicated that patients can experience monitoring as obtrusive and undesired, and that it can even lead to higher depression scores [ 118 ]. Several studies have focused on increasing the comfort level and decreasing the obtrusiveness of wearables to circumvent these problems, looking at the possibility to integrate bioimpedance measurements in clothing [ 54 ], the use of flexible and stretchable materials [ 119 ], and to increase battery life [ 82 ]. In some use cases, “nearables” could be used as an alternative to wearables, leading to invisible and effortless methods.…”

Section: Challenges and Outlookmentioning

confidence: 99%

See 1 more Smart Citation

Wearable Bioimpedance Monitoring: Viewpoint for Application in Chronic Conditions

Willemijn¹

2021

JMIR Biomed Eng

View full text Add to dashboard Cite

Currently, nearly 6 in 10 US adults are suffering from at least one chronic condition. Wearable technology could help in controlling the health care costs by remote monitoring and early detection of disease worsening. However, in recent years, there have been disappointments in wearable technology with respect to reliability, lack of feedback, or lack of user comfort. One of the promising sensor techniques for wearable monitoring of chronic disease is bioimpedance, which is a noninvasive, versatile sensing method that can be applied in different ways to extract a wide range of health care parameters. Due to the changes in impedance caused by either breathing or blood flow, time-varying signals such as respiration and cardiac output can be obtained with bioimpedance. A second application area is related to body composition and fluid status (eg, pulmonary congestion monitoring in patients with heart failure). Finally, bioimpedance can be used for continuous and real-time imaging (eg, during mechanical ventilation). In this viewpoint, we evaluate the use of wearable bioimpedance monitoring for application in chronic conditions, focusing on the current status, recent improvements, and challenges that still need to be tackled.

show abstract

Section: Application Areas Of Bioimpedance Monitoring For Chronic Con...mentioning

confidence: 99%

Section: Challenges and Outlookmentioning

confidence: 99%

Wearable Bioimpedance Monitoring: Viewpoint for Application in Chronic Conditions

Willemijn¹

2021

JMIR Biomed Eng

View full text Add to dashboard Cite

show abstract

“…(b) The non-respiratory power measured from the R-R intervals after the removal of the RSA, denoted by NRE. The following parameters were computed jointly from the filtered respiration and the RSA, describing their relationship: (a) The variation of the phase lag between the two, denoted by VPL, computed as the standard deviation of the slope of the phase lag similarly to [9]. (b) The synchronization of the phase lag as described in [7], denoted by SPL.…”

Section: Processingmentioning

confidence: 99%

Cardio:Respiratory Characterization of the Autonomic Balance

Mirmohamadsadeghi¹,

Bourdillon²,

Millet³

et al. 2016

2016 Computing in Cardiology Conference (CinC)

Self Cite

View full text Add to dashboard Cite

The autonomic balance is often measured using the low frequency (LF) and high frequency (HF) powers of the heart beat-to-beat intervals. However, these indices do not adequately integrate the influence of respiration and have been widely criticized. We studied the autonomic balance with measures from the heart beat-to-beat intervals taking into account the respiratory activity. Using cardiac and respiratory data acquired simultaneously from healthy volunteers in supine and orthostatic positions, we found that the investigated measures convey changes in the autonomic balance in a physiologically meaningful manner in contrast to the classic LF and HF indices. IntroductionThe cardiac autonomic balance, describing the activations of the sympathetic and parasympathetic branches of the autonomic nervous system (ANS), is often noninvasively measured through heart rate variability (HRV). In HRV analysis, which is the analysis of the heart inter-beat intervals variations, the powers in the low frequency (LF) band of the inter-beat intervals, between 0.04 and 0.15 Hz, believed to be influenced by both the sympathetic and parasympathetic branches of the ANS, and high frequency (HF) band between 0.15 and 0.4 Hz, thought to be influenced by the parasympathetic branch of the ANS, are measured as markers [1]. Furthermore, the ratio LF/HF of the powers is sometimes used as a marker of sympathetic activation [2,3]. However, the LF-HF partitioning and the use of the LF/HF marker are widely contested [3][4][5][6], in part because there is evidence against a clear linear separability of the activations of the two branches of the ANS, but also due to the influence of the respiration on the HRV [3][4][5]. The respiration may occur in the LF or the HF band, or jump from one to the other within a given experimental protocol, and since it has a large influence on the power of the inter-beat intervals, it cannot be ignored when performing HRV analysis. Some researchers have proposed to analyze the respiratory and non-respiratory HRV [4], while others propose to center the HF band on the respiratory frequency and to adjust the LF boundary accordingly [6].In addition to HRV analysis, the synchronization of the phase lag between the respiration and the respiratory component of the inter-beat intervals, referred to as the respiratory sinus arrhythmia (RSA), has been proposed as a potential autonomic index [7], taking root in ANS-mediated synchronization aspects of the cardio-respiratory system.In the present study, we aim to apply and compare respiration-corrected HRV analysis techniques in addition to investigating measures engulfing synchronization aspects of the respiration influence on the HRV. These measures are compared for the supine and orthostatic body positions, assumed to elicit parasympathetic and sympathetic dominance, respectively. We used electrocardiogram (ECG) and respiration data from healthy subjects. By least-squares identification, the RSA was extracted from the inter-beat intervals time series of the ECG. The RS...

show abstract

“…Characteristics of included studies (N=101). [[21][22][23]25,28,32,[34][35][36][39][40][41][42][43]45,46,49,53,56,59-65,67,69-71,73,74,76,78,80-83,85,86,88-90,93,95-97,99-101,104,106,108,109,114-119] 60 Journal article[3,24,26,27,[29][30][31]33,37,38,44,47,48,50,54,55,57,58,68,72,75,77,79,84,87,92,94,98,102,103,105,107,110,111,…”

mentioning

confidence: 99%

Smart Shirts for Monitoring Physiological Parameters: Scoping Review

Khundaqji

Hing

Furness

et al. 2020

JMIR Mhealth Uhealth

View full text Add to dashboard Cite

Background The recent trends of technological innovation and widescale digitization as potential solutions to challenges in health care, sports, and emergency service operations have led to the conception of smart textile technology. In health care, these smart textile systems present the potential to aid preventative medicine and early diagnosis through continuous, noninvasive tracking of physical and mental health while promoting proactive involvement of patients in their medical management. In areas such as sports and emergency response, the potential to provide comprehensive and simultaneous physiological insights across multiple body systems is promising. However, it is currently unclear what type of evidence exists surrounding the use of smart textiles for the monitoring of physiological outcome measures across different settings. Objective This scoping review aimed to systematically survey the existing body of scientific literature surrounding smart textiles in their most prevalent form, the smart shirt, for monitoring physiological outcome measures. Methods A total of 5 electronic bibliographic databases were systematically searched (Ovid Medical Literature Analysis and Retrieval System Online, Excerpta Medica database, Scopus, Cumulative Index to Nursing and Allied Health Literature, and SPORTDiscus). Publications from the inception of the database to June 24, 2019 were reviewed. Nonindexed literature relevant to this review was also systematically searched. The results were then collated, summarized, and reported. Results Following the removal of duplicates, 7871 citations were identified. On the basis of title and abstract screening, 7632 citations were excluded, whereas 239 were retrieved and assessed for eligibility. Of these, 101 citations were included in the final analysis. Included studies were categorized into four themes: (1) prototype design, (2) validation, (3) observational, and (4) reviews. Among the 101 analyzed studies, prototype design was the most prevalent theme (50/101, 49.5%), followed by validation (29/101, 28.7%), observational studies (21/101, 20.8%), and reviews (1/101, 0.1%). Presented prototype designs ranged from those capable of monitoring one physiological metric to those capable of monitoring several simultaneously. In 29 validation studies, 16 distinct smart shirts were validated against reference technology under various conditions and work rates, including rest, submaximal exercise, and maximal exercise. The identified observational studies used smart shirts in clinical, healthy, and occupational populations for aims such as early diagnosis and stress detection. One scoping review was identified, investigating the use of smart shirts for electrocardiograph signal monitoring in cardiac patients. Conclusions Although smart shirts have been found to be valid and reliable in the monitoring of specific physiological metrics, results were variable for others, demonstrating the need for further systematic validation. Analysis of the results has also demonstrated gaps in knowledge, such as a considerable lag of validation and observational studies in comparison with prototype design and limited investigation using smart shirts in pediatric, elite sports, and emergency service populations.

show abstract

Sleep apnea detection using features from the respiration and the ecg recorded with smart-shirts

Cited by 8 publications

References 18 publications

Wearable Bioimpedance Monitoring: Viewpoint for Application in Chronic Conditions

Wearable Bioimpedance Monitoring: Viewpoint for Application in Chronic Conditions

Cardio:Respiratory Characterization of the Autonomic Balance

Smart Shirts for Monitoring Physiological Parameters: Scoping Review

Contact Info

Product

Resources

About