Clinical Research Directory

Smartwatch Accuracy for Measuring Vitals and Anxiety Before Disc Surgery

This study aims to verify the accuracy of blood pressure, heart rate, blood oxygen saturation, anxiety level, and sleep cycle data measurements obtained from Samsung smartwatches compared to the currently accepted method used in patients with disc herniation undergoing the preoperative period.

Study of Daily Step Count and Treatment Response in Rectal Cancer (STEP-R)

This study aims to examine the impact of daily physical activity, specifically step count, on treatment outcomes and side effects in patients with locally advanced rectal cancer receiving total neoadjuvant therapy (chemotherapy and radiotherapy before surgery). Using Huawei Watch Fit 2 smartwatches, we will track participants' daily step counts, heart rate, and sleep quality. The primary hypothesis is that higher step counts and physical activity levels correlate with higher rates of complete pathological response at surgery. A secondary hypothesis is that increased physical activity may be associated with fewer or less severe side effects during treatment. Participants will wear a smartwatch and complete the EORTC QLQ-C30 Quality of Life Questionnaire and the Pittsburgh Sleep Quality Index at the beginning and end of treatment. Data from the smartwatch, including step count, heart rate changes, and sleep duration, will be reviewed weekly during routine visits. Approximately 200 patients with rectal cancer will participate, and each will be followed from the start of therapy until surgery (around 4-6 months). Total data collection is expected to take 12-15 months. This study could improve cancer care by identifying links between physical activity and treatment outcomes, supporting future exercise guidelines for oncology patients.

Smartwatch-Based AI Model for OSA Prediction (SWOSA)

This study aims to develop an artificial intelligence (AI) model for more accurately diagnosing obstructive sleep apnea (OSA) by collecting blood oxygen saturation and other health information during sleep using a smartwatch. OSA is common but often underdiagnosed, and the gold-standard diagnostic test, polysomnography, is costly and time-consuming. Smartwatches can provide a variety of health data, such as sleep patterns, blood oxygen saturation, and heart rate, which can help detect key symptoms and signs of OSA. By developing an AI model that uses smartwatch data to screen for OSA, this study seeks to offer a cost-effective and accessible diagnostic method, ultimately contributing to the early detection and improved treatment rates of OSA.

Effect of Smart Watch and App on PAP Adherence in OSA (Watch-OSA)

Continuous positive airway pressure (CPAP) is highly effective in treating obstructive sleep apnea (OSA). However, this treatment modality relies heavily on patient adherence, and poor adherence to the treatment limits its effectiveness in treating OSA. Strategies to augment adherence are needed in the management of OSA. The smart watch and linked app provide various health information, including sleep, snoring or oxygen saturation during sleep, exercise, blood pressure, and electrocardiogram. The smart watch and linked app could potentially improve adherence to positive airway pressure (PAP) treatment. This randomized controlled trial (RCT) aimed to examine whether the use of smart watch and app can increase PAP adherence in patients with OSA.