#Japan #Tokyo #rheumatoid arthritis #Tech Doctor #Wearable Devices

Tech Doctor Showcases Innovative Research on Wearable Data Utilization for Rheumatoid Arthritis in Major Conferences

In an exciting development for the medical research community, Tech Doctor Inc. has collaborated with Keio University’s Department of Internal Medicine (Rheumatology) on a groundbreaking study focused on rheumatoid arthritis patients. This research, which harnesses wearable technology, was presented at two prestigious international conferences in June 2026: the European League Against Rheumatism (EULAR) and the Federation of Clinical Immunology Societies (FOCIS).

Research Objectives and Approach

The objective of this study was to analyze data gathered from wearable devices—specifically the Google Fitbit—pertaining to physical activity, sleep patterns, and heart rate variability (HRV). Alongside this physical data, patient-reported outcomes (PROs) were also assessed. By employing machine learning technologies, researchers were able to objectively estimate patients' quality of life (QoL) and levels of fatigue from the collected data.

At EULAR, researchers presented their findings on the correlation between the QoL indicator EQ-5D and the wearable data collected. This session highlighted how wearable technology can provide valuable, real-time insights into patients' conditions, which are often missed with traditional assessment methods. At the FOCIS conference, the focus shifted to fatigue, revealing an impactful relationship between fatigue assessment tools (FACIT-F and BFI) and wearable device data.

This research was proudly supported by the Japan Medical Research and Development Agency (AMED), under the project aimed at developing a robust research infrastructure for preventive healthcare and innovative medical devices.

Background and Importance of the Study

Rheumatoid arthritis significantly affects patients not only through joint pain but also through fatigue, sleep disturbances, and depression. These factors drastically decrease quality of life, emphasizing the need for accurate and timely assessments. Traditional PRO approaches often rely on patient memory and the timing of assessments, making them prone to inconsistencies and inaccuracies.

Wearable devices have recently allowed for continuous monitoring of various biological data, such as activity levels, sleep quality, and heart metrics. Tech Doctor has previously reported on the utility of wearable-derived data in reflecting disease activity in rheumatoid arthritis, showing possible avenues for developing digital biomarkers that can objectively assess patient conditions.

In this study, 107 participants utilized the Fitbit Sense2 wristband to continuously gather data on their daily habits and biometrics. Connections between the data and quality of life indicators, as well as fatigue scores, were analyzed, along with machine learning support to estimate subjective patient experiences from objective data.

Key Findings

Significant findings emerged from this research, underscoring the feasibility of using wearable data as an instrumental tool in clinical assessments:

1. Correlation with Quality of Life:
During the EULAR 2026 Congress, it was demonstrated that the EQ-5D utility values correlated significantly with metrics such as daytime HRV, nighttime HRV, and sleep activity levels (METs x hours). Various EQ-5D domains, such as mobility and daily activities, showed meaningful associations with HRV indicators. Furthermore, a machine learning model that classified QoL states based on wearable data achieved high differentiation performance with an AUC-ROC of 0.75 to 0.89, reinforcing the model's predictive capability.

2. Link to Fatigue Measurements:
At the FOCIS 2026 Annual Meeting, researchers presented compelling results connecting fatigue scores (FACIT-F and BFI) with wearable data. Specifically, FACIT-F scores demonstrated significant correlations with resting heart rate and nighttime HRV. Meanwhile, BFI scores were notably correlated with both daytime and nighttime HRV. Classification models for fatigue groups yielded promising results with ROC-AUC scores of 0.88 for FACIT-F and 0.82 for BFI, confirming the potential of wearable data in recognizing fatigue levels among rheumatoid arthritis patients.

Implications and Future Directions

The results of this study illustrate the potential for wearable technology to serve as a digital biomarker, providing continuous and objective insights into patients' quality of life and fatigue levels in rheumatoid arthritis. As traditional evaluation methods sometimes fail to capture day-to-day symptom fluctuations, embedding wearable technology into standard patient monitoring practices could revolutionize disease management and treatment efficacy assessments.

Tech Doctor is committed to advancing the application of wearable data and machine learning in healthcare, pursuing improvement in data utilization in medical settings and fostering patient-centered care.

Conference Presentation Details

• - EULAR 2026 Congress

  — Period: June 3-6, 2026
  — Location: London, UK
  — Format: Poster Tour
  — Title: “Wearable-derived data and machine learning predict EQ-5D-based quality of life in patients with rheumatoid arthritis”
  — Website: EULAR Congress

• - FOCIS 2026 Annual Meeting

  — Period: June 9-12, 2026
  — Location: San Francisco, USA
  — Format: Poster Presentation
  — Title: “Subjective Fatigue Assessed by FACIT-F and BFI Questionnaires Correlates with Objective Wearable-Derived Data in Patients with Rheumatoid Arthritis”
  — Website: FOCIS Meeting

About Tech Doctor Inc.

Founded with the vision of creating a data-driven approach to health improvement, Tech Doctor Inc. is focused on developing digital biomarkers derived from daily sensing data through wearable devices. Collaborating with medical, pharmaceutical, and food industries, Tech Doctor aims to realize AI in healthcare, enabling innovative solutions for better patient outcomes.

Website: Tech Doctor