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AI-POWERED
GAIT ANALYSIS

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 anisteps is a patent pending, mobile first animal health application that assists in the early detection of canine health issues through gait assessment by analysing videos captured on a smartphone.

1

anisteps empowers dog owners, veterinarians and service dog handlers to monitor canine health through smartphone video-based gait analysis. Captured videos can be securely uploaded to a veterinary provider for further expert review, annotation, and diagnosis. 

2

In addition to detecting gait-related abnormalities that may indicate pain or illness, anisteps allows users to track key wellness metrics—such as BCS (Body Condition Scoring), diet, medication, worming, and exercise—providing a holistic view of a dog’s physical condition.

3

The anisteps app brings clinical-level mobility insights into the hands of everyday users without requiring expensive or inaccessible lab equipment.

Approach

Aspect
Traditional Methods
anisteps Approach
Environment
Clinic/lab setting; stress and unfamiliar surfaces alter gait
Captures gait naturally at home or outdoors via mobile app
Observation
Short, one-off snapshots during appointments
Continuous, longitudinal monitoring over days/weeks
Accuracy
Relies on human observation; subtle or early signs often missed
Objective, AI-powered analysis detects even minor asymmetries
Equipment
Expensive force plates, treadmills, or motion capture systems
Simple mobile app & camera; accessible to vets and owners
Cost & Accessibility
Tens of thousands of euros; limited to specialist centers
Affordable, scalable, and available to all practices & owners
Data & Insights
Limited metrics; no longitudinal tracking
Rich data, standardized metrics, trend analysis, ailment identification
Owner Involvement
Owners dependent on clinic visits
Owners can capture and share data easily from home
Impact on Outcomes
Conditions often diagnosed late, after significant deterioration
Early diagnosis enables timely intervention, reduced pain, better treatment outcomes, and lower long-term healthcare costs

Department of Electronic Engineering, Maynooth University, Ireland

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