Md Abdullah Al Rumon, Veeturi Suparna, Mehmet Seckin, Dhaval Solanki, K. Mankodiya
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In this work, we seamlessly integrate soft textile sensors into a T-shirt and develop a detachable and Wi-Fi-enabled (2.4GHz) bio-instrumentation board, creating a pervasive wireless system (WPS) for guided breathing exercises (GBE). The system features an intuitive graphical user interface (GUI) and a seamless IoT-based control and computing system (CCS). It offers real-time instructions for inhaling and exhaling at various breathing speeds, including slow, normal, and fast breathing. Functions such as filtering, peak detections for respiration, and heart rate analysis are computed conjointly at the sender and receiver ends. We utilized the Pan-Tompkins and custom algorithms to calculate HR and RR from the filtered time-series signals. We conducted a study with 10 healthy adult participants who wore the T-shirt and performed guided breathing exercises. The average respiration event (inhale-exhale) detection accuracy was ≈98%. We validated the recorded HR against the 3-lead standard ECG monitoring device, achieving an accuracy of ≈99%. The RR-HR correlation analysis showed an R square value of 0.987. Collectively, these results demonstrate Nisshash’s potential as a personal guided breathing exercise solution.","PeriodicalId":163556,"journal":{"name":"2023 IEEE International Conference on Smart Computing (SMARTCOMP)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Nisshash: Design of An IoT-based Smart T-Shirt for Guided Breathing Exercises\",\"authors\":\"Md Abdullah Al Rumon, Veeturi Suparna, Mehmet Seckin, Dhaval Solanki, K. Mankodiya\",\"doi\":\"10.1109/SMARTCOMP58114.2023.00019\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Breathing exercises are gaining attention in managing anxiety and stress in daily life. 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引用次数: 0
摘要
呼吸练习在管理日常生活中的焦虑和压力方面越来越受到关注。尤其是横膈膜呼吸法,能促进身心的平静。现有的方法,如冥想、瑜伽和引导呼吸的医疗设备,通常需要专家指导、复杂的仪器、笨重的设备和粘性电极。为了应对这些挑战,我们推出了Nisshash,一款基于物联网的智能t恤,为调节呼吸练习提供个性化解决方案。Nisshash内置了三通道电子纺织呼吸传感器和定制的模拟前端(AFE)板,可同时监测呼吸速率(RR)和心率(HR)。在这项工作中,我们将柔软的纺织品传感器无缝集成到t恤中,并开发了一个可拆卸的、支持wi - fi (2.4GHz)的生物仪器板,为引导呼吸练习(GBE)创建了一个普适无线系统(WPS)。该系统具有直观的图形用户界面(GUI)和无缝的基于物联网的控制和计算系统(CCS)。它为在各种呼吸速度下吸气和呼气提供实时指示,包括慢的、正常的和快速的呼吸。诸如滤波、呼吸峰值检测和心率分析等功能在发送端和接收端联合计算。我们利用Pan-Tompkins和自定义算法从滤波后的时间序列信号中计算HR和RR。我们对10名健康的成年参与者进行了一项研究,他们穿着t恤,进行有指导的呼吸练习。平均呼吸事件(吸入-呼出)检测准确率≈98%。我们将记录的HR与3导联标准心电监护装置进行验证,准确率达到约99%。RR-HR相关分析R平方值为0.987。总的来说,这些结果证明了Nisshash作为个人指导呼吸练习解决方案的潜力。
Nisshash: Design of An IoT-based Smart T-Shirt for Guided Breathing Exercises
Breathing exercises are gaining attention in managing anxiety and stress in daily life. Diaphragmatic breathing, in particular, fosters tranquility for both body and mind. Existing methods, such as meditation, yoga, and medical devices for guided breathing, often require expert guidance, complex instruments, cumbersome devices, and sticky electrodes. To address these challenges, we present Nisshash, an IoT-based smart T-shirt offering a personalized solution for regulated breathing exercises. Nisshash is embedded with three-channel e-textile respiration sensors and a tailored analog front-end (AFE) board to simultaneously monitor respiration rate (RR) and heart rate (HR). In this work, we seamlessly integrate soft textile sensors into a T-shirt and develop a detachable and Wi-Fi-enabled (2.4GHz) bio-instrumentation board, creating a pervasive wireless system (WPS) for guided breathing exercises (GBE). The system features an intuitive graphical user interface (GUI) and a seamless IoT-based control and computing system (CCS). It offers real-time instructions for inhaling and exhaling at various breathing speeds, including slow, normal, and fast breathing. Functions such as filtering, peak detections for respiration, and heart rate analysis are computed conjointly at the sender and receiver ends. We utilized the Pan-Tompkins and custom algorithms to calculate HR and RR from the filtered time-series signals. We conducted a study with 10 healthy adult participants who wore the T-shirt and performed guided breathing exercises. The average respiration event (inhale-exhale) detection accuracy was ≈98%. We validated the recorded HR against the 3-lead standard ECG monitoring device, achieving an accuracy of ≈99%. The RR-HR correlation analysis showed an R square value of 0.987. Collectively, these results demonstrate Nisshash’s potential as a personal guided breathing exercise solution.