Workload management through glanceable feedback: The role of heart rate variability

J. Muñoz, Fábio Pereira, E. Karapanos
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引用次数: 7

Abstract

The active monitoring of workload levels has been found to significantly reduce work-related stress. Heart rate and heart rate variability (HRV) measurements via photoplethysmography (PPG) sensors have shown a strong potential to accurately describe daily workload levels. However, due its complexity, HRV is commonly misunderstood and the associated measurements are rarely incorporated for workload monitoring in novel technological devices such as smartwatches and activity trackers. In this paper we explore the potential of consumer-grade smartwatches, equipped with PPG sensors, to assist in the active monitoring of workload during work hours. We develop a prototype that employs the SDNN index, a powerful HRV marker for cardiac resilience to differentiate between high and low workload levels along the work day, and presents feedback in glanceable form, by highlighting workload levels and physical activity over the past hour in 5-minutes blocks at the periphery of the smartwatch. A field study with 9 participants and 3 variations of our prototype attempts to quantify the impact of the HRV feedback over subjective and objective workload as well as users' engagement with the smartwatch. Results showed workload levels as inferred from the PPG sensor to positively correlate with self-reported workload and HRV feedback to result to lower levels of workload as compared to a conventional activity tracker. Moreover, users engaged more frequently with the smartwatch when HRV feedback was presented, than when only physical activity feedback was provided. The results suggest that HRV as inferred from PPG sensors in wearables can effectively be used to monitor workload levels during work hours.
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通过可查看的反馈进行工作量管理:心率变异性的作用
研究发现,主动监测工作量水平可以显著减少工作压力。通过光电容积脉搏波(PPG)传感器测量心率和心率变异性(HRV),显示出准确描述日常工作负荷水平的强大潜力。然而,由于其复杂性,HRV通常被误解,相关测量很少被纳入智能手表和活动追踪器等新型技术设备的工作量监测中。在本文中,我们探讨了配备PPG传感器的消费级智能手表的潜力,以协助在工作时间主动监控工作量。我们开发了一个原型,该原型采用SDNN指数(一种强大的心率波动指标,用于区分工作日的高负荷和低负荷水平),并通过在智能手表的外围显示过去一小时内5分钟内的工作量水平和身体活动,以可浏览的形式呈现反馈。我们对9名参与者和3种不同的原型进行了实地研究,试图量化HRV反馈对主观和客观工作量以及用户对智能手表的参与度的影响。结果显示,与传统的活动追踪器相比,从PPG传感器推断的工作量水平与自我报告的工作量和HRV反馈呈正相关,从而导致更低的工作量水平。此外,当HRV反馈出现时,用户使用智能手表的频率比只提供体力活动反馈时更高。结果表明,从可穿戴设备中的PPG传感器推断的HRV可以有效地用于监测工作时间的工作量水平。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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