PhysIQ Receives FDA Clearance for Algorithm Of Patients’ Continuous Ambulatory Respiration Rates

PhysIQ fda clearance
Image: PhysIQ

PhysIQ, a company known for applying Artificial Intelligence (AI) in wearable sensor data, received FDA 510(k) clearance for an algorithm facilitating cloud-based analysis of patients’ continuous ambulatory respiration rates. This regulatory clearance adds to the company’s expanding portfolio of FDA-cleared cloud-based analytics, which also include QRS detection, heart rate, heart rate variability, atrial fibrillation detection, and their personalized physiology change detection analytic.

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PhysIQ’s algorithms collect raw telemetry from the device and uploads it to the cloud where FDA-cleared analytics use the raw biosignals to produce vital signs. With this approach physIQ is able to provide vital sign analytics that benefit from the superior computing power of the cloud and fuel the higher-level analytics that further characterize dimensions of human physiology, reports Business Wire.

“In a real-world environment, respiration rate is a tough vital sign to accurately and consistently measure given high levels of motion artifact,” said Matt Pipke, co-founder and CTO of physIQ. “Given these challenges, it is ideal to be able to capitalize on the vast processing power and memory in the cloud to iron out the edge cases and outliers.”

A man sleeping

Wearable sensors have enormous potential to transform how we understand and manage human health. However, these on-body sensors are collecting data in a noisy environment and, without sophisticated methods to manage signal noise, the resulting output is compromised.

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“Accurate and precise vital signs are an essential component of a clinical grade remote intelligence solution but, ultimately, these vital signs are an input into the higher-level AI-based analytics for which physIQ is known,” said Gary Conkright, chairman and CEO of physIQ. “We are encouraged by the successful clearance of respiration as a core dimension of human cardiopulmonary physiology which will accelerate our development of further AI analytics.”