通过无线电波反射利用智能手机的生物识别信息进行压力评估

Suzumi Sato, Hayato Shimano, Megumi Saito, Shigeru Shimamoto, N. Kobayashi
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引用次数: 0

摘要

智能手机可用于操作物联网设备和访问智能手机游戏等服务,但长时间使用会导致游戏障碍。世界卫生组织(WHO)于 2022 年将游戏障碍列为国际疾病。游戏障碍是一种无法控制每天游戏时间的症状。近年来,游戏障碍患者人数不断增加,而医院却没有足够的能力来治疗他们,因此有必要在不去医院的情况下自己治疗游戏障碍。因此,有必要了解用户在玩游戏时所承受的压力,并在合理范围内提供鼓励休息等补救措施。由于本文是一项初步研究,因此对用户在玩智能手机游戏时的压力进行评估。为了利用生物识别信息评估压力,我们通过将 2.4 GHz 频段的无线电波反射到胸部,获得无线电波强度的时间变化,并通过信号处理获得脉搏波和呼吸波,从中得出 17 个可归因于压力的参数。从一个月的智能手机使用记录中,提取出每月平均游戏时间较短的 16 名受试者和每月平均游戏时间较长的 18 名受试者。由于可以假定平均游戏时间短和平均游戏时间长的两组用户在游戏过程中的压力状态不同,因此使用压力诱发参数比较游戏过程中的变化差异,并使用机器学习进行二元分类,以评估用户的压力状态。由于这种方法使用的是 2.4GHz 频段的两根天线,因此今后有可能使用智能手机测量压力,从而有助于了解可能在无意识中承受的压力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Stress Evaluation with Biometric Information Using Smartphone by Radio Wave Reflection
Smartphone can be used to operate IoT devices and access services such as smartphone game, but prolonged use cause gaming disorder. Gaming disorder was published as an international disease in 2022 by World Health Organization (WHO). Gaming disorder is a symptom of an inability to control the amount of time spent playing games daily. In recent years, the number of patients with gaming disorder has been increasing and there are not enough hospitals to treat them, so it is necessary to cure gaming disorder by oneself without visiting hospitals. Therefore, it is necessary to understand the stress that users are under while playing games, and to provide remedial measures such as encouraging rest within a reasonable range. Since this paper is an initial study, stress evaluation of users during smartphone game playing. To evaluate the stress using biometric information, we obtain temporal changes in radio wave intensity by reflecting radio waveform in the 2.4 GHz band to the chest, and pulse wave and respiration waveforms by signal processing, from which 17 parameters that are attributable to stress. From the one-month smartphone usage logs, 16 subjects with short average game time per month and 18 subjects with long average game time per month are extracted. Since it can be assumed that the stress state during game play differs between the groups with short and long average game time, comparison of the difference in variation during game play using stress-induced parameters and binary classification using machine learning to evaluate the user's stress state. Since this method uses two antennas in the 2.4GHz band, it will be possible to measure stress using smartphones in the future, contributing to the understanding of stress that is likely to be held unconsciously.
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