A medical-grade intelligent sleep mattress, which uses fiber optic sensors to real-time, non-intrusive monitoring of the elderly's heart rate/breathing rate, in/out of bed, sleep habits, etc. The data is uploaded in real-time to the system, and if the elderly experiences an abnormality, an alarm is generated quickly.
Based on the characteristics of accurate monitoring and non-contact, the monitoring mattress can be widely used in various in-bed or lying down monitoring scenarios, such as sleep analysis, continuous health monitoring and screening, centralized care monitoring, remote health care, continuous mental stress analysis, etc., to meet various non-contact physiological monitoring needs.
Ø The intelligent monitoring mattress uses fiber optic sensing combined with high-precision acceleration proprietary detection technology, to achieve high-precision detection of human physiological and movement signals without contact: heart rate, breathing, movement, in bed and out of bed, etc.
Ø Using proprietary precise algorithms, a variety of human body data can be accurately analyzed as needed: heart rate frequency, breathing frequency, and assist various application systems to calculate sleep habits.
Ø The intelligent monitoring mattress can output monitoring results in real-time or at customer-specified frequencies through communication methods such as the IoT (2G\4G), WiFi, etc. based on different application scenarios. It can connect to server in local area network or internet cloud based on Socket.
Function | Monitoring Range/Specification | Description | Remark |
Heart Rate Accuracy | Detection range: under normal vital signs, 50 ~ 120 times/m, deviation range ±5 times/m, whichever is greater; Compared with medical monitor, the time when the deviation is within ±5 should not be less than 90% per day. | The comparison scenario is the subject lying in a supine, resting state |
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Breathing Rate Accuracy | Detection range: under normal vital signs, 10 ~ 30 times/m, deviation range ±4 times/m, whichever is greater; Compared with medical monitor, the time when the deviation is within ±2 should not be less than 98% per day. | The comparison scenario is the subject lying in a supine, resting state |
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Heart Rate | 50～120 times/m | Output stable values within 20 seconds after the body is still, and update the values per second within the previous 30 seconds every 5 seconds |
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Breathing Rate | 10～30 times/m | Output stable values within 30 seconds after the body is still, and update the values per second within the previous 30 seconds every 5 seconds |
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In/out of bed | Support | Fast mode responds within 10 seconds, delay mode responds within 20 seconds |
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Sleep analysis | Provide sleep analysis and scoring rules | Implemented on the server based on the rules | Need to be supported by the application platform |
Body motion detection | Support，can output 3 levels for body motion amplitude | responds within 5 seconds(slight, moderate, significant) |
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