Non-contact Dual Pulse Doppler System Based Real-time Relative Demodulation and Respiratory &amp; Heart Rates Estimations for Chronic Heart Failure Patients

Tran, Vinh Phuc; Al-Jumaily, Adel

doi:10.1016/j.procs.2015.12.274

Cited by 5 publications

(8 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The current achievements are summarized in Table 2. 2013-2015 [14,15,[38][39][40] Heart rate variability Error between 3-11% for single antenna, and 1-6% for dual antenna.…”

Section: Challenges and Future Research Directionsmentioning

confidence: 99%

“…Studies have reported some commendable achievements, such as error of less than 0.5 breath per minute for respiratory rate and one beat per minute for heart rate [26,27,61]. In addition, the achieved accuracy of Doppler radar in measuring physiological parameters, such as respiratory rate is 92% [39], heart rate is 88% [39,59,81] to 91% [40], and with the addition of harmonics interference, the average error can be reduced further to 3.2% [84]. However, conventional FFT may not always be able to reliably separate the rich sinusoidal components due to smearing and leakage problems, particularly from the limited data samples [74].…”

Section: Time-frequency Analysismentioning

confidence: 99%

“…The relative demodulation technique provides real-time DC offsets, clutters, and null-points automatic elimination. The technique also approximates the instantaneous derivatives of the subject's chest periodic motions with the separation of the instantaneous subject's respiratory and heart periodic displacements [40]. The relative demodulation equation that governs the extraction of the chest motions velocity (v(t)) is given in (10) and (11).…”

Section: Phase-nulling Cancellationmentioning

confidence: 99%

“…The ranges of the reported filter bandwidth frequencies for respiratory rate are from 0.1-0.5 Hz which is equivalent to 6-30 breaths per minute. The heart rate frequencies are from 0.8-2.0 Hz which is equivalent to 48-120 beats per minute [13,26,32,39,40,59,61,63,65,69].…”

Section: Time-frequency Analysismentioning

confidence: 99%

See 3 more Smart Citations

Doppler Radar-Based Non-Contact Health Monitoring for Obstructive Sleep Apnea Diagnosis: A Comprehensive Review

Tran

Al-Jumaily

Islam

2019

BDCC

Self Cite

View full text Add to dashboard Cite

Today’s rapid growth of elderly populations and aging problems coupled with the prevalence of obstructive sleep apnea (OSA) and other health related issues have affected many aspects of society. This has led to high demands for a more robust healthcare monitoring, diagnosing and treatments facilities. In particular to Sleep Medicine, sleep has a key role to play in both physical and mental health. The quality and duration of sleep have a direct and significant impact on people’s learning, memory, metabolism, weight, safety, mood, cardio-vascular health, diseases, and immune system function. The gold-standard for OSA diagnosis is the overnight sleep monitoring system using polysomnography (PSG). However, despite the quality and reliability of the PSG system, it is not well suited for long-term continuous usage due to limited mobility as well as causing possible irritation, distress, and discomfort to patients during the monitoring process. These limitations have led to stronger demands for non-contact sleep monitoring systems. The aim of this paper is to provide a comprehensive review of the current state of non-contact Doppler radar sleep monitoring technology and provide an outline of current challenges and make recommendations on future research directions to practically realize and commercialize the technology for everyday usage.

show abstract

“…The current achievements are summarized in Table 2. 2013-2015 [14,15,[38][39][40] Heart rate variability Error between 3-11% for single antenna, and 1-6% for dual antenna.…”

Section: Challenges and Future Research Directionsmentioning

confidence: 99%

Section: Time-frequency Analysismentioning

confidence: 99%

Section: Phase-nulling Cancellationmentioning

confidence: 99%

Section: Time-frequency Analysismentioning

confidence: 99%

See 2 more Smart Citations

Doppler Radar-Based Non-Contact Health Monitoring for Obstructive Sleep Apnea Diagnosis: A Comprehensive Review

Tran

Al-Jumaily

Islam

2019

BDCC

Self Cite

View full text Add to dashboard Cite

show abstract

“…To compensate for any noises and/or unwanted body movements, the subject's predicted tidal volume (V pt ) in milliliters must be calculated to be used as the artefacts rejection criteria. According to Stahl [9], Livingston and Lee [10], "V pt " can be expressed in form of "allometric" formula, where "Wt" and "Ht" as described above in relation to (11):…”

Section:   mentioning

confidence: 99%

Non-contact real-time estimation of intrapulmonary pressure and tidal volume for chronic heart failure patients

Tran

Al-Jumaily

2016

2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

Self Cite

View full text Add to dashboard Cite

Long-term continuous patient monitoring is required in many health systems for monitoring and analytical diagnosing purposes. It has been recognized that these types of monitoring systems have shortcomings related to patient comfort and/or functionality. Non-contact monitoring systems have been developed to address some of these shortcomings. One of such systems is non-contact physiological vital signs assessments for Chronic Heart Failure (CHF) patients. This paper presents a novel pulmonary ventilation model that defines the relationship between the intrapulmonary pressure and the chest displacement. A novel intrapulmonary pressure and tidal volume estimation algorithm is also proposed. A database consisting of twenty CHF patients with New York Heart Association (NYHA) Heart Failure Classification Class II & III; whose underwent full Polysomnography (PSG) analysis for diagnosis of sleep apnea, disordered sleep, or both, was selected for the verification of the proposed model and algorithm. The proposed algorithm analyzes the non-contact sensor data and estimate the patient's intrapulmonary pressure and tidal volume. The output of the algorithm is compared with the gold-standard PSG recordings. Across all twenty CHF patients' recordings with mean recorded sleep duration of 7.76 hours, the tidal volume estimation median accuracy achieved 83.13% with a median error of 57.32 milliliters. A potential application would be non-contact continuous monitoring of intrapulmonary pressure and tidal volume during sleep in the home.

show abstract

Monitoring of nocturnal central sleep apnea in Heart failure patients using noncontact respiratory differences

Khushaba

Armitstead

Schindhelm

2017

2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

View full text Add to dashboard Cite

Monitoring of respiration patterns allows the early detection of various breathing disorders and may better identify those at risk for adverse acute outcomes in a variety of clinical settings. In this paper, we report on the use of SleepMinder (SM), a bedside non-contact Doppler-based biomotion recording sensor, to monitor remotely the nocturnal respiration patterns of 50 patients with systolic Heart failure (HF) while undergoing a lab based Polysomnography (PSG) test. A new respiration rate (RR) monitoring algorithm was developed based on the collected overnight radar signals. Two schemes of RR scoring were utilized: respiratory rate count (RRC) and instantaneous respiratory rates (IRR). Analysis of SM vs. PSG revealed that the mean/median IRR scored by SM is highly correlated with that scored on the nasal flow/effort signals from the corresponding PSG studies on all patients, with a significant correlation coefficient of 0.98 (average absolute difference of 0.31 breaths/min), and 0.97 (p<;0.01, average absolute difference of 0.38 breaths/min) for the median and mean of RR respectively. Our experimental results also show that the difference between the RR estimations from IRR and RRC schemes can be utilized to identify central sleep apnea (CSA)/Cheyne-Stokes respiration (CSR) sections without additional apnea detection modules. As a result, with a sensitivity and specificity of 71% and 88% respectively, and an accuracy of 86%, our CSA/CSR screener, plugged with our RR estimation, can play an important role in the remote management of HF patients.

show abstract

Non-contact Dual Pulse Doppler System Based Real-time Relative Demodulation and Respiratory & Heart Rates Estimations for Chronic Heart Failure Patients

Cited by 5 publications

References 2 publications

Doppler Radar-Based Non-Contact Health Monitoring for Obstructive Sleep Apnea Diagnosis: A Comprehensive Review

Doppler Radar-Based Non-Contact Health Monitoring for Obstructive Sleep Apnea Diagnosis: A Comprehensive Review

Non-contact real-time estimation of intrapulmonary pressure and tidal volume for chronic heart failure patients

Monitoring of nocturnal central sleep apnea in Heart failure patients using noncontact respiratory differences

Contact Info

Product

Resources

About