A team from the ITACA Institute at the Universitat Politècnica de València has assessed vulnerability and anxiety in elderly cancer patients. By combining data obtained from wearable devices and validated questionnaires, the research enabled the development of dynamic risk models based on artificial intelligence.
These models analyse the evolution of factors such as physical activity and sleep quality, providing a more precise and personalised view of each patient’s situation.
Among its conclusions, the study indicates that, within the studied population, irregular sleep patterns are associated with a higher risk of anxiety and depression; low levels of exercise are linked to increased susceptibility to functional decline; and patients with metastatic prostate cancer are at a greater risk of vulnerability compared to those with other types of cancer.
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This study is part of the European project LifeChamps, which involved 121 patients diagnosed with breast cancer, prostate cancer, or melanoma from Greece, Sweden, Spain, and the United Kingdom. The research was conducted by Zoe Valero Ramón, Gema Ibáñez Sánchez, Antonio Martínez Millana and Carlos Fernández Llatas, researchers from the SABIEN-ITACA group, and its results were published in the scientific journal Sensors.
“Older adults who have survived cancer face additional challenges due to age, such as multimorbidity, frailty, and the psychosocial impacts of the disease. These factors can affect their treatment and hinder their ability to recover,” explains Zoe Valero, lead author of the study.
To better understand this situation, the UPV team analysed the relationship between data obtained from wearable devices and patient well-being using advanced process mining techniques. The goal was to develop dynamic risk models to more accurately identify vulnerability and anxiety in cancer patients.
“Devices such as the Fitbit Charge 4 and the Withings Body+ smart scale were used to record objective data on activity and sleep. Meanwhile, the questionnaires allowed assessment of anxiety and patient-reported vulnerability. This approach has shown us that risk factors are not static, but evolve over time,” notes Gema Ibáñez, researcher at the ITACA Institute.
Less exercise, more fatigue, and greater functional decline
One of the most relevant findings of the study was the relationship between physical activity and vulnerability. Patients with a sedentary lifestyle were found to have a higher risk of frailty. Specifically, those with lower physical activity throughout the study demonstrated a greater tendency towards fatigue and functional decline, underscoring the importance of promoting regular exercise in this population.
Irregular sleep, anxiety and depression
The study also found that irregular sleep patterns, characterised by variations in sleep quality, were associated with an increased risk of anxiety and depression. Sleep cycle instability negatively affected the emotional well-being of patients, “suggesting that sleep monitoring could play a key role in their psychological care,” according to ITACA-UPV researchers.
Prostate metastasis: more vulnerable
Furthermore, the study revealed that patients with prostate metastases had a significantly higher risk of vulnerability compared to those with other types of cancer. This finding highlights the need for specific intervention strategies targeting this patient subgroup, aiming to improve their quality of life and reduce their level of frailty.
Wearable devices and AI to improve healthcare
This study demonstrates the potential of wearable devices and artificial intelligence to improve healthcare through dynamic risk assessment models.
“The process mining-based methodology allowed us to identify risk factors with greater accuracy and flexibility, which could optimise clinical decision-making,” emphasises Antonio Martínez Millana, researcher at the ITACA Institute.
Although the sample size and study duration are limitations, the results provide a solid foundation for future research in remote health monitoring. In particular, this work highlights the potential of wearable devices to analyse the relationship between activity, sleep, and vulnerability in cancer patients.
“The methodology used is adaptable and replicable in different contexts. Its application in other chronic diseases, such as diabetes or heart disease, could facilitate personalised interventions and improve clinical outcomes,” concludes Carlos Fernández Llatas.