Institute of Computer Science and Engineering, College of Computer Science, National Chiao Tung University, 1001 University Road, Hsinchu, Taiwan.
Department of Computer Science, College of Computer Science, National Chiao Tung University, 1001 University Road, Hsinchu, Taiwan.
J Med Syst. 2019 Mar 5;43(4):94. doi: 10.1007/s10916-019-1221-9.
Individuals with Internet gaming disorder (IGD) frequently play online games to achieve satisfaction. Numerous signal processing questions regarding the negative consequences and characteristic respiration in a long-term sitting posture remain unanswered. This study recruited 50 individuals with high-risk and low-risk IGD (HIGD and LIGD); these participants were taught to perform a specific respiration during game-film stimuli. The instantaneous frequencies on abdominal movement (f) were calculated with ensemble empirical mode decomposition (EEMD). The difference value (Δf) between rest and stimulus statuses was calculated and found that HIGD showed Δf values of 0.060 during positive stimuli and 0.055 during negative stimuli before the exercise but 0.020 and 0.016, respectively, after the exercise. However, the Δf value for those with LIGD during negative stimuli before the exercise was 0.013, and it increased to 0.025 after the exercise. This is the first approach to IGD discrimination toward abdominal response with EEMD.
个体若患有网络游戏障碍（IGD），则常沉迷于网络游戏以获得满足感。目前仍有许多关于长期坐姿所带来的负面影响和特征性呼吸的信号处理问题尚未得到解答。本研究招募了 50 名患有高风险和低风险 IGD（HIGD 和 LIGD）的个体；这些参与者被教导在游戏电影刺激下进行特定的呼吸。通过集合经验模态分解（EEMD）计算腹运动的瞬时频率（f）。计算休息和刺激状态之间的差值（Δf），发现 HIGD 在积极刺激时的Δf 值为 0.060，在消极刺激时为 0.055，但在运动前为 0.020 和 0.016，而在运动后分别为 0.020 和 0.016。然而，LIGD 在运动前消极刺激时的Δf 值为 0.013，运动后增加到 0.025。这是使用 EEMD 对 IGD 进行腹部反应区分的首次尝试。
