Participants were seated comfortably in a car seat that was mounted on a six-degrees-of-freedom motion platform (MB-E-6DOF/12/1000, Moog Inc.). They were restrained safely with a 4-point harness, and their heads were supported by a head support with lateral arms to limit head movements (Black bear, Matrix Seating Ltd.). Participants wore a virtual reality head-mounted display (HMD, Oculus Rift CV1) and noise-canceling headphones (Sony WH-1000XM3). A green fixation point was presented in the HMD and remained at a fixed distance (66 cm) in front of the participant throughout the experiment (i.e., it moved with the participant during self-motion stimuli). The participants were instructed to keep their heads straight and still and to focus on the fixation point throughout the experiment. The participants initiated trials and reported their selections via a response box (Cedrus RB-540).
Wh 1000xm3
Manufactured by Sony
Sourced in Japan
The WH-1000XM3 is a pair of wireless noise-cancelling headphones developed by Sony. The device features advanced noise-cancelling technology and supports high-resolution audio playback.
Automatically generated - may contain errors
Lab products found in correlation
4 protocols using wh 1000xm3
1
Motion Perception in Virtual Reality
2
Auscultation of Cardiopulmonary Sounds
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Finally, the participants in the control group auscultated 16 cardiopulmonary sounds using noise-cancelling headphones (WH-1000XM3; Sony Corp., Tokyo, Japan). The participants in the intervention group auscultated 16 cardiopulmonary sounds like the control group using the proposed support system in a test session (Figure 3 and Supplementary Movie Material including the first 2 questions out of the 16 questions in the test session). Here, the 16 cardiopulmonary sounds were a combination of four cardiac sounds (i.e. normal, aortic stenosis, aortic regurgitation, and mitral regurgitation sounds) and four pulmonary sounds (i.e. normal, fine crackles, coarse crackles, and wheeze sounds). Each cardiopulmonary sound consists of four locations: second intercostal space at the right sternal border (No. 3, red mark of the auscultation place in Figure 2 ), second intercostal space at the left sternal border (No. 4 in Figure 2 ), apex (No. 8 in Figure 2 ), and ipsilateral apex (No. 7 in Figure 2 ). Each cardiopulmonary sound was played for 60 seconds. During the test session, all participants filled in forms to indicate the types of sounds they recognized.
3
Heart Rate Variability During Recovery
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The HRR and HRV testing was completed independently by two professionals, and the relevant test methods and precautions were explained to each participant before the test. The HRV measurement system Ubpuse T1 (Biospace, Korea) was used to measure the HRV index 0–1 min before the warm‐up. During the recovery period (0–16 min after the cycling test), the participants in all four groups listened to piano songs on a headset (Sony WH‐1000XM3, Japan) at four different speeds according to their group assignment, as shown in Table 2 . A timer was started immediately after the cycling test ended, and each participant's HRV index was measured 0–1, 5–6, 10–11, and 15–16 min after exercise (see Table 1 ).
4
Equalizing Digit Recognition Probability
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Digits were equalized according to their recognition probability. Equalizing digits by applying level corrections to the digits ensured that each digit had a 50% chance of being recognized correctly at the same SNR. To do so, we recruited 20 normal-hearing (both ears) participants aged 20–33 years, with pure-tone thresholds <20 dB HL from 250 to 8,000 Hz. A custom Matlab script was used to generate the sequences of digits superimposed with noise on a laptop (MacBook Pro) that were presented monaurally through circumaural headphones (Sony WH1000XM3). Four lists of 10 digits were successively presented at 10 different SNRs decreasing from −2 to −20 dB in 2 dB steps. For each SNR level the 10 digits were presented randomly. The noise started 500 ms before and finished 500 ms after each digit. The participant was forced to choose a digit, even if it was not recognized (forced-choice procedure). The psychometric curves of recognition for each digit were fitted with a logistic function to determine the speech reception threshold (SRT, i.e., the SNR corresponding to a 50% recognition probability (Figure 1 ). Each digit's recording level was then adjusted using the difference between the SRT of each digit and the average SRT of all the digits (±0.4 dB maximum).
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