Key result
An error reduction algorithm mixing thermistor and elastic chest band data improved real-time estimation of cardiac vagal activity during body motion for interactive computer graphics.
A novel algorithm combining thermistor and elastic chest band data with Berger's interpolation enables accurate real-time estimation of cardiac vagal activity even during body motion.
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May aid motion-robust RSA monitoring in interactive systems; leaves open clinical validation.
Autonomic nervous system is important to maintain homeostasis, and respiratory sinus arrhythmia (RSA) is known as a selective index of cardiac vagal activity. In this paper, we evaluated errors in the amplitude of RSA under the condition of body motion (keyboard typing and mental arithmetic with touching panel) and proposed a method for reducing them. It was found that elastic chest band is suitable under the quiet condition, while thermistor is suitable under the condition of body motion. It was also found that Berger's interpolation method was the best for detecting instantaneous heartbeat intervals in real-time signal processing. Furthermore, we proposed a error reduction algorithm by mixing the data of thermistor and elastic chest band , and applied it for interactive CG (Computer Graphics) system that reflected the amplitude of RSA estimated in real-time.
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Kotani et al. (2007) studied Cardiac vagal activity estimation. Error reduction algorithm mixing thermistor and elastic chest band data was evaluated on Errors in the amplitude of respiratory sinus arrhythmia (RSA) under body motion. An error reduction algorithm mixing thermistor and elastic chest band data improved real-time estimation of cardiac vagal activity during body motion for interactive computer graphics.
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