Skip to main content
PD

Pedal Data

Pedal Data develops insole sensors integrated with AI algorithms to provide objective, quantifiable gait analysis for mobility assessment. This digital health solution enables early detection, risk stratification, and continuous monitoring of gait abnormalities, particularly for Parkinson's disease management. The technology supports value-based care by facilitating personalized interventions and measuring patient outcomes efficiently.

East New York, United StatesFounded 2024210+ followers
Updated 4 months ago

Funding

$120K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.

Funding rounds are not available yet.

Founders

Product

Problem

Individuals with Parkinson's disease often experience gait abnormalities that impact their mobility and quality of life. Detecting these changes early is challenging, and current methods lack the ability to continuously monitor gait patterns in real-world settings.

Solution

Pedal Data offers a gait analysis system that utilizes insole sensors and AI algorithms to monitor and quantify gait dynamics in individuals with Parkinson's disease. The insole sensors capture foot motion measurements, including linear acceleration and angular velocity, providing a comprehensive understanding of gait. The AI algorithms analyze this data to deliver real-time insights into gait abnormalities and assess the severity of any detected changes. This system enables early detection of gait abnormalities, facilitating personalized interventions to slow disease progression and improve patient outcomes.

Target Audience

The primary users are clinicians and researchers focused on Parkinson's disease, seeking objective and continuous gait analysis for early detection, personalized treatment plans, and monitoring disease progression.

Features

  • Insole sensor that captures multiple foot motion measurements, including linear acceleration and angular velocity
  • AI algorithms that provide real-time analysis of gait dynamics and severity scoring
  • Continuous, non-intrusive monitoring of gait in real-world settings
  • Remote monitoring capabilities that minimize the need for frequent in-person visits
  • Quantifiable metrics related to gait, such as stride length, step count, and foot clearance
  • Integration into insole designs for comfort and unobtrusiveness
This profile is AI-generated and may contain inaccuracies.