Affiliations: [a] Department of Medical Oncology, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China | [b] Department of Computer Science and Engineering, Zhejiang University City College, Hangzhou, Zhejiang, China | [c] Department of Surgical Oncology, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China | [d] College of Computer Science and Technology, Zhejiang University, Zhejiang, China
Correspondence:
[*]
Corresponding author: Xian Zhong, Second Affiliated Hospital, Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou 310009, Zhejiang, China. Tel.: +86 571 87784795; Fax: +86 571 87767088; E-mail:zhongxian_2000@163.com
Abstract: BACKGROUND: Fatigue is the most common symptom associated with
cancer and its treatment, and profoundly affects all aspects of quality of
life for cancer patients. It is very important to measure and manage
cancer-related fatigue. Usually, the cancer-related fatigue scores, which
estimate the degree of fatigue, are self-reported by cancer patients using
standardized assessment tools. But most of the classical methods used for
measurement of fatigue are subjective and inconvenient. OBJECTIVE: In this study, we try to establish a new method to
assess cancer-related fatigue objectively and accurately by using smart
bracelet. METHODS: All patients with metastatic pancreatic cancer wore smart
bracelet for recording the physical activity including step count and sleep
time before and after chemotherapy. Meantime, their psychological state was
assessed by completing questionnaire tables as cancer-related fatigue
scores. RESULTS: Step count record by smart bracelet reflecting the
physical performance dramatically decreased in the initial days of
chemotherapy and recovered in the next few days. Statistical analysis showed
a strong and significant correlation between self-reported cancer-related
fatigue and physical performance (P= 0.000, r=-0.929). Sleep time was also
significantly correlated with fatigue (P= 0.000, r= 0.723). Multiple
regression analysis showed that physical performance and sleep time are
significant predictors of fatigue. CONCLUSIONS: Measuring activity using smart bracelets may be an
appropriate method for quantitative and objective measurement of
cancer-related fatigue by using smart bracelet devices.
