Key Features

We developed biosignals monitoring mobile app specifically tailored to the needs of our client’s smart clothing for health monitoring. The app offers seamless access to real-time biosignals recorded from smart clothing. It enables users to actively monitor their health and take preventive or corrective actions to manage stress and mitigate the risk of fatal conditions.

The key features of the mobile app include:

Stress monitoring

Tracks physiological indicators of stress, such as skin temperature, EEG, ECG, and heart rate, to determine the optimum zone for people doing workouts. It provides users real-time data on their stress levels and notifies them about deviations.

Fitness tracking

Alongside monitoring physical activity, calorie count, and exercise performance, the app offers enhanced insights into muscle usage during workouts. Users can visualize the activation of different muscle groups in real-time and aim for more targeted and efficient workouts.

Integration with smart clothing

Seamlessly integrates with intelligent clothing sensors to gather biometric data and sync with the mobile app for centralized data analysis and visualization.

Actionable insights

The mobile interface presents stress and fitness data captured from smart clothing in an actionable format. It allows users to make informed decisions about their physical and mental well-being.

Predictive analytics

We developed advanced algorithms to anticipate health pattern changes and alert users when it’s time to slow down and hydrate. It ensures optimal performance and well-being. This feature allows fitness and healthcare professionals to implement personalized interventions for better lifestyle and health outcomes.

Smart clothing connectivity

Through the user’s personal account, seamless integration allows for adding new smart tech clothing items while providing real-time monitoring of battery status for connected garments.

Smart clothing application data dashboard
Development of an e-textile based mobile app for real-time health monitoring

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