Disruptive Wearables are Game Changers for Dementia DCTs focused on Diverse Populations.

Transformative DCT $25 Wearables in real world environment drive new models of access and data collection.

This white paper describes how new breakthrough technology demonstrably changes the approach to Decentralized Clinical Trials (DCTs) focused on Alzheimer’s disease and related dementia (ADRD) therapeutics including gait based ADRD detection and ongoing monitoring. Current and historical challenges of DCTs, like patient recruitment, retention, safety, cost, equipment recovery are highly exacerbated when strategizing approaches to implementing Diverse Population DCTs. Additionally, new hinderances may appear in the way of logistics, patient acceptance, technology challenges and device sustainability. With an amazing pipeline of dementia therapeutics coming to the fore, the need for longitudinal DCTs is critical, which further magnifies these implementation challenges for diverse populations.


Consequently, this white paper presents a new DCT paradigm that outlines a package of technologies with the aim to revolutionize the approach to performing ADRD focused DCTs within diverse communities. The breakthrough technology aspects include:


  • A wearable device cost basis of $25, or 5% of current DCT wearables with similar functionality
  • Battery life of up to 6 months, making the wearable “disposable.”
  • “Coin Cell” form factor.
  • Integration of data collection from off wearable sensors providing Activities of Daily Living (ADLs) data (Bed, Bathroom, prescription adherence, presence detection, etc.)
  • Integration with RPM (Remote Patient Monitoring) devices.
  • 100% Bluetooth and Cellular Backhaul (no Wi-Fi needed)
  • Over the Air (OTA) Dynamic algorithmic changes delivered to wearables
  • AI algorithmic matching – post 30-day environmental Machine Learning
  • Patient selection of form factor and style – driving adherence
  • No charge cradle required.
  • No USB transfer required.


Further, the capabilities of this technology for these specific purposes do not guarantee outsize performance gains over existing wearable DCT benchmarks. Breakthrough success must utilize the supporting tools and strict adherence to rules based algorithmic validation. This white paper will also describe the necessary operational philosophies that this technology enables to optimize a continual cycle of material advances in performance.


  • “Reason to Wear” …For DCT Patient safety to be inherent to the process and the patient, the wearable device must be simultaneously a commercial aging safety product and a DCT platform.
  • “Caregiver Alerts” …For successful DCT usage adherence to be the normative outcome, the wearable learning curve must benefit both the patient and the patient’s caregiving community.
  • “Platform Connectivity” …To truly drive the furtherance of the dementia research community, there is a continual pursuit of novel digital endpoints, which must include personalized, blended ADL data, longitudinally.
  • “External/Internal Validation” …To truly be able to have generalizability of trial results, there must a broader collection of novel digital endpoints to utilize machine learning for empirical determination.
  • “Continuous Improvement” … AI algorithms driving DCTs involving fall prevention and dementia diagnosis/monitoring must use holistic digital endpoints from wearables and ADLs, longitudinally.
  • “Break Environmental Dependencies”… Dementia based DCT performance gains will plateau unless gait data generated by wearables have almost complete context of home layout, this only achieved by integrated off board (not on wearable) sensors.
  • “AI Over the Air”…Gait sampling bias will lead to predictive performance gain plateaus; unless, wearable gait resolution can be altered, over the air, automatically through cumulative AI, without concern of loss of battery life.
  • “Novel Source Data”… Novel input of longitudinal trendlines will be the determinant factors of both the usability and efficacy of determinative, predictive AI dementia algorithms.
  • “Longitudinal Paramount”…For ultra longitudinal patient adherence, the patient and family also must have longitudinal benefits and overwhelming cost/benefit outcomes.
  • “Human Element “…Longitudinal AI algorithms must intersperse human observation notes, and notes must be easy to record, with opportunities numerical scoring.


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