Abstract

BackgroundCancer-related fatigue is a serious side effect of cancer, and its treatment can disrupt the quality of life of patients. Clinically, the standard method for assessing cancer-related fatigue relies on subjective experience retrieved from patient self-reports, such as the Brief Fatigue Inventory (BFI). However, most patients do not self-report their fatigue levels.ObjectiveIn this study, we aim to develop an objective cancer-related fatigue assessment method to track and monitor fatigue in patients with cancer.MethodsIn total, 12 patients with lung cancer who were undergoing chemotherapy or targeted therapy were enrolled. We developed frequency-domain parameters of heart rate variability (HRV) and BFI based on a wearable-based HRV measurement system. All patients completed the BFI-Taiwan version questionnaire and wore the device for 7 consecutive days to record HRV parameters such as low frequency (LF), high frequency (HF), and LF-HF ratio (LF-HF). Statistical analysis was used to map the correlation between subjective fatigue and objective data.ResultsA moderate positive correlation was observed between the average LF-HF ratio and BFI in the sleep phase (ρ=0.86). The mapped BFI score derived by the BFI mapping method could approximate the BFI from the patient self-report. The mean absolute error rate between the subjective and objective BFI scores was 3%.ConclusionsLF-HF is highly correlated with the cancer-related fatigue experienced by patients with lung cancer undergoing chemotherapy or targeted therapy. Beyond revealing fatigue levels objectively, continuous HRV recordings through the photoplethysmography watch device and the defined parameters (LF-HF) can define the active phase and sleep phase in patients with lung cancer who undergo chemotherapy or targeted chemotherapy, allowing a deduction of their sleep patterns.

Highlights

  • BackgroundFatigue is a reminder of the requirement of energy reimbursement in normal individuals

  • We aim to develop objective cancer-related fatigue criteria based on heart rate variability (HRV)

  • We obtained the low frequency (LF)-high frequency (HF) ratio from HRV data collected from a wearable device with photoplethysmography (PPG) sensors to achieve this goal

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Summary

Introduction

BackgroundFatigue is a reminder of the requirement of energy reimbursement in normal individuals. Cancer-related fatigue imposes limitations on the normal daily activities of several patients with cancer and profoundly affects all aspects of their quality of life, including compliance with standard treatments such as chemotherapy or radiotherapy [4]. The standard method for assessing cancer-related fatigue relies on subjective experience retrieved from patient self-reports, such as the Brief Fatigue Inventory (BFI). Methods: In total, 12 patients with lung cancer who were undergoing chemotherapy or targeted therapy were enrolled. Conclusions: LF-HF is highly correlated with the cancer-related fatigue experienced by patients with lung cancer undergoing chemotherapy or targeted therapy. Beyond revealing fatigue levels objectively, continuous HRV recordings through the photoplethysmography watch device and the defined parameters (LF-HF) can define the active phase and sleep phase in patients with lung cancer who undergo chemotherapy or targeted chemotherapy, allowing a deduction of their sleep patterns

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