Deploying and Examining Beacon for At-Home Patient Self-Monitoring with Critical Flicker Frequency

Research Background and Problem

• Problem and Challenges: Chronic liver disease can lead to hepatic encephalopathy (HE), a neurological impairment that may result in cognitive decline and even death. Diagnosing minimal hepatic encephalopathy (MHE) is particularly challenging, as current clinical detection methods are not widely adopted, involve high costs, require specialized personnel, and lack standardized testing protocols. Existing diagnostic tools are bulky, expensive, and difficult for patients to operate independently.

• Significance: Early detection and intervention for MHE (e.g., adjusting medication dosage) can significantly improve patients' quality of life and reduce the risk of progression to overt hepatic encephalopathy (OHE). Extending diagnostic technology to patients' homes for daily monitoring can provide timely data support for patients, caregivers, and physicians.

• Research Motivation: Literature indicates that critical flicker frequency (CFF) is an effective indicator for diagnosing MHE, but there is a lack of convenient and patient-friendly self-measurement devices. This study aims to develop a low-cost, portable, and user-friendly device called "Beacon" to enable frequent testing in home environments.

Solution

• Method and Approach: The study proposes an innovative device named Beacon, which allows users to measure their critical flicker frequency (CFF) at home. Beacon consists of a hardware device and a companion mobile application, providing a more stable and precise measurement environment.

• Innovations:

  • Expanding traditional clinical CFF testing into a self-monitoring tool.
  • Modular hardware design using 3D-printed components to reduce manufacturing errors, with improved physical aesthetics (designed as an adjustable lamp-like device to reduce users' resistance to medical equipment).
  • Offering multiple measurement protocols (e.g., ascending method MOL-D and forced-choice method FC) while optimizing visualization and interpretation of measurement data.

• Implementation Steps and Key Technologies:

  1. Hardware design improvements, including achieving high brightness and stable flicker stimuli, along with low-power batteries to support long-term uninterrupted operation.
  2. Software development, featuring a mobile application and cloud-based health monitoring dashboard for multi-platform compatibility and remote data storage.
  3. Deployment phase: Conducting a six-week home measurement experiment with 21 chronic liver disease patients and analyzing the temporal consistency and environmental robustness of the data.
  4. Data visualization development: Designing various charts to present measurement results, showcasing measurement history and trends to patients and clinicians.

Research Outcomes

• Specific Results:

  • The device was successfully deployed in patients' homes, with 21 patients participating in the six-week measurement experiment, and 15 completing interviews. Both patients and physicians acknowledged Beacon's ease of use and the potential significance of its measurement data.
  • The study found that the two measurement methods (MOL-D and FC) have distinct advantages: MOL-D has shorter measurement times but higher data variance, while FC is more accurate but slightly longer in duration.

• Advantages over Existing Solutions:

  • Beacon is portable, low-cost, and user-friendly, eliminating the complexity and bulkiness of traditional CFF measurement devices.
  • It enables stable long-term measurements in home environments, overcoming the limitations of previous tools that were restricted to clinical settings.

• Experimental or Evaluation Results:

  • Data showed high acceptance of the device among the 15 interviewed patients, especially regarding the ease of use in home settings. Compared to typical clinical devices (e.g., Lafayette Flicker Fusion System), most patients preferred Beacon's compact design.
  • Analysis of measurement data at different time points revealed that CFF data remained relatively stable and reliable in patients' daily lives, demonstrating feasibility across diverse environments.
  • User research on data visualization design indicated patients preferred simpler and more intuitive representations, with a strong desire to view measurement values and historical data directly.

• Limitations and Future Directions:

  • Limitations: The current study's participants were primarily liver disease patients, especially those with high motivation due to transplant needs, which may limit the applicability of results to other patient groups or the general population. Additionally, the direct correlation between CFF data and specific treatment decisions has not been thoroughly explored.
  • Future Directions:
    1. Further research on integrating CFF measurement data into daily life decisions, such as driving behavior and medication adjustments.
    2. Exploring the potential application of Beacon for other chronic diseases (e.g., Alzheimer's disease).
    3. Optimizing data presentation methods to develop more interpretable and actionable visualization tools for patients and medical teams.
    4. Investigating how Beacon can better support collaboration between caregivers and patients, alleviating tension in medication decision-making.

Through this study, Beacon demonstrates significant potential in the field of home health monitoring, providing patients with an innovative tool for self-management while paving the way for enhanced collaboration between families and healthcare systems.