PurposeTo determine the impact of noise on heart rate variability (HRV) in men, with a focus on the noise type rather than on noise intensity.Materials and MethodsForty college-going male volunteers were enrolled in this study and were randomly divided into four groups according to the type of noise they were exposed to: background, traffic, speech, or mixed (traffic and speech) noise. All groups except the background group (35 dB) were exposed to 45 dB sound pressure levels. We collected data on age, smoking status, alcohol consumption, and disease status from responses to self-reported questionnaires and medical examinations. We also measured HRV parameters and blood pressure levels before and after exposure to noise. The HRV parameters were evaluated while patients remained seated for 5 minutes, and frequency and time domain analyses were then performed.ResultsAfter noise exposure, only the speech noise group showed a reduced low frequency (LF) value, reflecting the activity of both the sympathetic and parasympathetic nervous systems. The low-to-high frequency (LF/HF) ratio, which reflected the activity of the autonomic nervous system (ANS), became more stable, decreasing from 5.21 to 1.37; however, this change was not statistically significant.ConclusionThese results indicate that 45 dB(A) of noise, 10 dB(A) higher than background noise, affects the ANS. Additionally, the impact on HRV activity might differ according to the noise quality. Further studies will be required to ascertain the role of noise type.
This paper presents a sliding mode control method for wheeled mobile robots. Because of the nonlinear and nonholonomic properties, it is difficult to establish an appropriate model of the mobile robot system for trajectory tracking. A robust control law which is called sliding mode control is proposed for asymptotically stabilizing the mobile robot to a desired trajectory. The posture of the mobile robot (including the position and heading direction) is presented and the kinematics equations are established in the two-dimensional coordinates. According to the kinematics equations, the controller is designed to find an acceptable control law so that the tracking error will approximate 0 as the time approaches infinity with an initial error. The RFID sensor space is used to estimate the real posture of the mobile robot. Simulation and experiment demonstrate the efficacy of the proposed system for robust tracking of mobile robots.
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