This fall-detection model is perfect to add into wrist-worn devices. It is specifically developed to understand motion and recognize falling, and at the same time reduce battery consumption to a minimum, so that the wearable maintains a long battery life.
This model provides safety features for all users, but is particularly useful for seniors.
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The Coughing model is designed for use in healthcare products or wearables. It detects coughing, which can indicate illness or other respiratory conditions, and can be used to identify potential environmental hazards.
- Captures at least 84-94% of coughs
- Robust against the most common indoor and outdoor background sounds
- Measures coughs per hour to identify 'sick' versus 'healthy' user
This model is ideal for companies with healthcare or wearable products that want to identify snoring. This important feature can be used to identify health or environmental issues.
- Captures more than 89-96% of snores
- Robust against the most common background sounds, particularly indoor
- Flexibly designed to be used in wearables or in devices that are placed near the bed
This model uses audio event detection to identify emergency vehicle sirens. This can be used to alert pedestrians to emergency vehicles in their vicinity, or to trigger other safety features in wearables.
- Captures over 80-95% of siren sounds
- Robust against common traffic background sounds in different environments
- Able to detect siren sounds from all directions