PMID- 26737221
OWN - NLM
STAT- MEDLINE
DCOM- 20160909
LR  - 20200928
IS  - 2694-0604 (Electronic)
IS  - 2375-7477 (Linking)
VI  - 2015
DP  - 2015
TI  - Non-contact dual pulse Doppler system based respiratory and heart rates 
      estimation for CHF patients.
PG  - 4202-5
LID - 10.1109/EMBC.2015.7319321 [doi]
AB  - Long term continuous patient monitoring is required in many health systems for 
      monitoring and analytical diagnosing purposes. Most of monitoring systems had 
      shortcomings related to their functionality or patient comfortably. Non-contact 
      continuous 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 
      automated estimation algorithm for the non-contact physiological vital signs 
      assessments for CHF patients based on a patented novel non-contact biomotion 
      sensor. A database consists of twenty CHF patients with New York Heart 
      Association (NYHA) heart failure Classification Class II & III, whose underwent 
      full Polysomnography (PSG) analysis for the diagnosis of sleep apnea, disordered 
      sleep, or both, were selected for the study. The patients mean age is 68.89 
      years, with mean body weight of 86.87 kg, mean BMI of 28.83 (obesity) and mean 
      recorded sleep duration of 7.78 hours. The propose algorithm analyze the 
      non-contact biomotion signals and estimate the patients' respiratory and heart 
      rates. The outputs of the algorithm are compared with gold-standard PSG 
      recordings. Across all twenty patients' recordings, the respiratory rate 
      estimation median accuracy achieved 92.4689% with median error of +/- 1.2398 
      breaths per minute. The heart rate estimation median accuracy achieved 88.0654% 
      with median error of +/- 7.9338 beats per minute. Due to the good performance of 
      the propose novel automated estimation algorithm, the patented novel non-contact 
      biomotion sensor can be an excellent tool for long term continuous sleep 
      monitoring for CHF patients in the home environment in an ultra-convenient 
      fashion.
FAU - Tran, Vinh Phuc
AU  - Tran VP
FAU - Ali Al-Jumaily, Adel
AU  - Ali Al-Jumaily A
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
PL  - United States
TA  - Annu Int Conf IEEE Eng Med Biol Soc
JT  - Annual International Conference of the IEEE Engineering in Medicine and Biology 
      Society. IEEE Engineering in Medicine and Biology Society. Annual International 
      Conference
JID - 101763872
SB  - IM
MH  - Aged
MH  - Algorithms
MH  - Female
MH  - Heart Failure/*physiopathology
MH  - *Heart Rate
MH  - Humans
MH  - Male
MH  - Middle Aged
MH  - Monitoring, Physiologic/*methods
MH  - Movement
MH  - *Respiratory Rate
MH  - *Sleep
MH  - Sleep Apnea Syndromes
MH  - Sleep Wake Disorders
EDAT- 2016/01/07 06:00
MHDA- 2016/09/10 06:00
CRDT- 2016/01/07 06:00
PHST- 2016/01/07 06:00 [entrez]
PHST- 2016/01/07 06:00 [pubmed]
PHST- 2016/09/10 06:00 [medline]
AID - 10.1109/EMBC.2015.7319321 [doi]
PST - ppublish
SO  - Annu Int Conf IEEE Eng Med Biol Soc. 2015;2015:4202-5. doi: 
      10.1109/EMBC.2015.7319321.