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Time series forecasting of cardiopulmonary signals during exercise

Shodhganga@INFLIBNET

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Title Time series forecasting of cardiopulmonary signals during exercise
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Contributor Shah Vipul A
 
Subject Adaptive filter, ARMAX, Bruce protocol, Cardiopulmonary system overload,Time series forecasting, Incremental Exercise,NARNET,NLARX ,RMSE, Treadmill test
 
Description quotExercise-based evaluation of the cardiopulmonary system is always advisable over other
newlineinvasive and costly diagnostics procedures. It has enough potential to judge the fitness of
newlinehealthy persons as well as to detect symptoms of abnormality earlier. In the incremental
newlineexercise, amount of workload increases at every few minutes interval, so after initial
newlinestages, the amount of workload to the cardiac system is above average so sometimes it may
newlineoverload the cardiopulmonary system and this is not tolerable every time especially when
newlinethe subject is a cardiac patient. This research work presents a new approach for forecasting
newlineof cardiopulmonary signals after the premature end of the test. Here, three models are
newlineimplemented which are the Adaptive filter, the Autoregressive moving average with
newlineexogenous terms (ARMAX) and the nonlinear ARX (NLARX), for time series forecasting
newlineof signals like Instant heart rate (HR) and respiration rate (RR). The models are
newlineimplemented such that it utilizes subject s own past and current responses to forecast
newlinefuture response, there is no need of another database for training or any other purpose.
newlinePerformance of these models are tested on normal as well as abnormal cardiac subjects.
newlineThe normal database is collected with the help of young subjects facing physical stress
newlinelevel of exercise protocol BRUCE on Treadmill machine and abnormal cardiac patients
newlinedatabase are collected from the online physiological database of PhysioNet. After
newlinevalidation of results and statistical analysis of forecasting errors, the NLARX model is
newlinefound to be more accurate and reliable for forecasting of cardiopulmonary signals like
newlineInstant HR and Instant RR for both kinds of subjects, Normal as well as Abnormal. The
newlineperformances of these three models ranked in descending order are: NLARX, ARMAX,
newlineand Adaptive filter. Additionally, the prediction algorithm is implemented for single step
newlineand multi-step-ahead (five step ahead) prediction of Instant RR with the help of artificial
newlineneural network structure- nonlinear autoreg
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Date 2018-10-04T05:39:21Z
2018-10-04T05:39:21Z
29-01-2014
24-08-2018
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Type Ph.D.
 
Identifier http://hdl.handle.net/10603/218379
 
Language English
 
Rights university
 
Format —
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None
 
Coverage —
 
Publisher Ahmedabad
Gujarat Technological University
Instrumentation and Control Engineering
 
Source University