New study in Letterkenny, Co Donegal aims to create an accurate baseline for this debilitating symptom, enabling the development of better predictive models and interventions

A team of researchers from Letterkenny Institute of Technology (LYIT) and Letterkenny University Hospital (LUH) will be using a novel continuous monitoring platform to accurately assess fatigue in individuals with breast cancer.  This study will be led by LYIT research lecturers Dr. William Scott and Dr. James Connolly in association with LUH research oncology nurse Mary Grace Kelly and consultant oncologist Dr. Karen Duffy.

“Cancer-related fatigue (CRF) – which is distinct from normal tiredness that may be resolved by periods of sleep or rest – is a well-recognised symptom of malignant breast disease. In fact, it may affect up to 70% of those undergoing therapy or deemed to be in remission,” said Dr. Scott. “This type of fatigue recurs unpredictably and can result in unavoidable and unforeseen reduction in quality of life for those individuals affected. Management of this condition can also place significant financial burden on health and social care facilities.”

“Previous research studies have suggested that modulations in the levels of certain plasma or salivary markers may be involved in the advancement of CRF symptoms. However, results from these studies are often conflicting and no individual marker or group of markers has been attributed to the cause of this fatigue. This has major implications for the development of predictive models of recurrence and the design of potential physiological and pharmacological interventions,” added Dr. Connolly.

The LYIT LUH study aims to address failure of earlier to studies to identify an accurate baseline for fatigue. Study participants will wear one a Verisenses’ Inertial Measurement Unit (IMUs) on their wrist to monitor their sleep patterns and activity levels continuously throughout the study.

This sensor does not require regular charging – its battery lasts for up to six months. Also, activity data is automatically uploaded to a remote cloud platform without any patient involvement, making it a low-stress, no-hassle device.

The novel wearable sensor platform will improve the efficiency and management of this feasibility study through speed of data collection, as well as remote monitoring of patient participation.