Integrated sensing hardware
A functional smart-insole system combining pressure sensors, motion sensing, embedded electronics, wireless communication and real-world data capture.
EigenSole
An AI-powered smart wearable that turns foot-pressure and motion data into useful insights for fitness, movement and long-term health tracking.
About the project
EigenSole began with a simple observation: the foot carries a large amount of information about how the body moves, loads, balances and responds over time, but most of this data remains invisible in everyday life.
The product is being developed primarily as a fitness and movement tracker, using plantar-pressure and motion data to provide insight into gait, balance, posture, loading patterns and activity. Unlike conventional wearables that focus mainly on the wrist, EigenSole looks at the point where the body interacts with the ground.
The longer-term opportunity extends beyond fitness. Changes in pressure distribution, symmetry, movement and loading can also be relevant to rehabilitation, injury recovery, fall-risk assessment, diabetic-foot monitoring and other health-related applications. The aim is to build a wearable platform that supports immediate fitness insights while creating a foundation for more clinically meaningful monitoring over time.
Product journey
EigenSole developed from early prototyping through hardware architecture, sensor integration, on-device processing, data acquisition, software visualisation and ML-assisted analytics.
Development brought together hardware, software, sensing, additive manufacturing, research collaborators and clinical inputs. Product demonstrations and validation informed continued development of the integrated system and customised insole designs.
The work remains at the prototype and product-development stage; the healthcare applications described here are development directions, not claims of clinical efficacy.
Need → prototype → hardware/software integration → validation → iteration
How it works
EigenSole combines pressure sensors, motion sensing, environmental measurements, embedded electronics, wireless communication, AI algorithms and user-facing software in one integrated hardware-software system.
The insole captures plantar-pressure and motion data during standing, walking and other activities. The embedded system processes and transmits this information to software interfaces, where the data can be visualised as pressure maps, gait patterns, loading trends, balance indicators and movement-related metrics.
AI and signal-processing algorithms are used to interpret the raw measurements and identify patterns that are difficult to understand from individual sensor values alone. The hardware, analytics and software are developed together so that the product can move from data capture towards meaningful feedback for users, trainers, clinicians and researchers.
Foot pressure and motion → embedded sensing → AI analytics → fitness and health insights
What the work produced
The project has resulted in a working foundation for an AI-powered wearable platform spanning hardware, software, analytics and product development.
AI-powered analytics software
Algorithms and interfaces for interpreting plantar pressure, gait, balance, posture, loading patterns and activity-related movement data.
Fitness-to-health product pathway
A product direction that begins with fitness and movement tracking while creating a longer-term foundation for rehabilitation, preventive care and clinically relevant monitoring.
Let’s talk about what you’re building.
I’m open to conversations about deeptech ventures, technical products and technical delivery across AI/ML, engineering software, simulation and connected hardware.