Designing adaptive integral sliding mode control for heart rate regulation during cycle-ergometer exercise using bio-feedback

Argha, Ahmadreza; Su, Steven W.; Nguyen, Hung T.; Celler, Branko G.

doi:10.1109/embc.2015.7319927

Cited by 8 publications

(2 citation statements)

References 9 publications

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“…A commonly used application for HR models is control of HR on a treadmill (Mazenc et al, 2010 ; Nguyen et al, 2011 ; Pătraşcu et al, 2014 ; Hunt and Fankhauser, 2016 ; Hunt and Liu, 2017 ), on a bicycle ergometer (Mohammad et al, 2012 ; Paradiso et al, 2013 ; Argha et al, 2014 , 2015a , b ; Leitner et al, 2014 ), for gait training (Koenig et al, 2011 ) or to control strain in exergames (Sinclair et al, 2009 ). Even apart from strain or stress control, use of HR models is conceivable for many other areas like training planning (Brzostowski et al, 2013 ; Schäfer et al, 2015 ), generating individualized training zones based on past training sessions, keeping track of performance development and adjustment of HR training zones, potentially enhancing accuracy by predicting the HR after a model is individualized and adjust the displayed HR according to measurement and model prediction, compensate missing or incorrectly detected HR values [see Jang et al ( 2016 )], and more.…”

Section: Modeling and Prediction Of Heart Ratementioning

confidence: 99%

Measurement, Prediction, and Control of Individual Heart Rate Responses to Exercise—Basics and Options for Wearable Devices

et al. 2018

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The use of wearable devices or “wearables” in the physical activity domain has been increasing in the last years. These devices are used as training tools providing the user with detailed information about individual physiological responses and feedback to the physical training process. Advantages in sensor technology, miniaturization, energy consumption and processing power increased the usability of these wearables. Furthermore, available sensor technologies must be reliable, valid, and usable. Considering the variety of the existing sensors not all of them are suitable to be integrated in wearables. The application and development of wearables has to consider the characteristics of the physical training process to improve the effectiveness and efficiency as training tools. During physical training, it is essential to elicit individual optimal strain to evoke the desired adjustments to training. One important goal is to neither overstrain nor under challenge the user. Many wearables use heart rate as indicator for this individual strain. However, due to a variety of internal and external influencing factors, heart rate kinetics are highly variable making it difficult to control the stress eliciting individually optimal strain. For optimal training control it is essential to model and predict individual responses and adapt the external stress if necessary. Basis for this modeling is the valid and reliable recording of these individual responses. Depending on the heart rate kinetics and the obtained physiological data, different models and techniques are available that can be used for strain or training control. Aim of this review is to give an overview of measurement, prediction, and control of individual heart rate responses. Therefore, available sensor technologies measuring the individual heart rate responses are analyzed and approaches to model and predict these individual responses discussed. Additionally, the feasibility for wearables is analyzed.

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Section: Modeling and Prediction Of Heart Ratementioning

confidence: 99%

Measurement, Prediction, and Control of Individual Heart Rate Responses to Exercise—Basics and Options for Wearable Devices

et al. 2018

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“…Sliding Mode Control (SMC) has its share here for HR control due to its well-known robustness. An event-driven Adaptive Integral Sliding Mode Control (AISMC) is designed in the study of Argha et al [13] to control the HR during a cycle-ergometer exercise. Their results were based on a LTV first order HR model.…”

Section: Introductionmentioning

confidence: 99%

A Barrier Function-Based Integral Sliding Mode Control of Heart Rate During Treadmill Exercise

MohammadRidha¹,

Al-Samarraie²

2023

MMEP

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The objective of this work is to design an Integral Sliding Mode Controller based on barrier function (ISMCbf) for a human Heart Rate (HR) during a treadmill exercise. ISMCbf commands the speed of the treadmill such that the individual HR follows a time-varying profile. This profile is pre specified as part of rehabilitation exercises for patients with cardiovascular diseases. ISMCbf is chosen due to its well-known robustness properties as well as to its simple design procedure as compared to classic SMC and ISMC. It does not require the upper bounds of the uncertainties and perturbations in its design. Moreover, it does not have discontinuous function, hence it is a chattering-free controller. ISMCbf designed in this work for the first time for this system and its performance is compared to Quasi SMC (QSMC) and Super Twisting SMC (STSMC) from previous studies. The simulated exercises were conducted on a nonlinear model describing HR response to the walking speed of a treadmill. For ISMCbf, the model parameters and their upper bound of uncertainties are considered unknown. During two different exercise scenarios, the three controllers guided HR to follow the time-varying reference profile. However, ISMCbf showed higher quantitative performance by recording less Integral Squared Error (ISE) and Integral Time Absolute Error (ITAE) indices as compared to the other controllers.

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Signal Compression Method Based Heart Rate Model Estimation and SMCSPO Control for Cardiac Rehabilitation with Treadmill

Young

Lee

2018

Intelligent Robotics and Applications

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Designing adaptive integral sliding mode control for heart rate regulation during cycle-ergometer exercise using bio-feedback

Cited by 8 publications

References 9 publications

Measurement, Prediction, and Control of Individual Heart Rate Responses to Exercise—Basics and Options for Wearable Devices

Measurement, Prediction, and Control of Individual Heart Rate Responses to Exercise—Basics and Options for Wearable Devices

A Barrier Function-Based Integral Sliding Mode Control of Heart Rate During Treadmill Exercise

Signal Compression Method Based Heart Rate Model Estimation and SMCSPO Control for Cardiac Rehabilitation with Treadmill

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