Happy Health, Inc. · Class II · Cleared Jun 18, 2025
| K-number | K242224 |
| Device name | Happy Health Home Sleep Test |
| Applicant | Happy Health, Inc. |
| Product code | MNR |
| Device class | Class II |
| Decision date | Jun 18, 2025 |
| Decision | Substantially Equivalent |
| Regulation | 868.2375 |
The Happy Health Home Sleep Test is a software-as-a-medical-device that processes data from wearable devices (specifically a smart ring with PPG and accelerometer sensors) to record and analyze biophysical parameters for evaluating sleep-related breathing disorders in adults aged 22 and older. It computes an Apnea Hypopnea Index (hAHI) and total sleep time to aid clinicians in diagnosing sleep apnea in clinical and home settings.
The subject device is a SaMD product designed to work with compatible external hardware devices, whereas the predicate (NightOwl) is a wearable device combining hardware and software. Both use PPG and accelerometer signals to compute AHI and total sleep time via proprietary algorithms based on peripheral arterial tone (PAT) detection, though the subject device uses a PAT-derived hAHI while the predicate uses pAHI. Both comply with IEC 62304 software standards.
IEC 62304 (medical device software development), FDA Guidance for Software Contained in Medical Devices, FDA Guidance on Cybersecurity in Medical Devices, FDA Guidance for Applying Human Factors and Usability Engineering, and American Academy of Sleep Medicine (AASM) guidelines for manual polysomnography scoring.
Both the subject and predicate devices are Class II breathing frequency monitors with identical product codes and regulations. Clinical validation demonstrates the subject device's hAHI correlates strongly with manually scored PSG-AHI (regression slope 0.98, R=0.98, Bland-Altman limits -9.8 to 10.7 events/hr), which meets the same performance criteria as the predicate (regression slope 0.9981). The TST performance (mean absolute difference 24.9 minutes) is comparable to the reference device (30.8 minutes). The architectural difference—SaMD versus integrated hardware-software—does not raise new safety or effectiveness questions since the compatible hardware uses identical sensor technology and the algorithms produce equivalent clinical outputs.
View the full FDA submission: accessdata.fda.gov