HoneyNaps Develops Wireless Sleep Monitoring System With Four Skin Patches

September 05, 2026
HoneyNaps has developed a wireless polysomnography system that replaces more than 24 wired sensors with four skin patches and uses AI to analyze sleep data.
HoneyNaps Develops Wireless Sleep Monitoring System With Four Skin Patches
Image: HoneyNaps via PR Newswire

HoneyNaps announced in a press release that it has developed a wireless polysomnography system using four skin patches and AI analysis. The head, chest, body, and leg sensors consolidate functions typically handled by more than 24 wired sensors.

The patches collect EEG, EOG, ECG, EMG, respiratory airflow, blood oxygen saturation, body position, and physical activity data. HoneyNaps' SOMNUM software analyzes the data for sleep stages, apnea events, arousals, and periodic limb movements.

The system includes flexible circuitry, an analog to digital converter, wireless noise reduction, electrostatic discharge protection, and a low power design. Its edge computing functions support real time processing and connections to centralized hospital systems, with possible use in home sleep testing and remote monitoring.

We hope you enjoyed this article.

Consider subscribing to one of our newsletters like Life AI Weekly or Daily AI Brief.

Also, consider following us on social media:

Healthcare & Life Sciences AI AI Brief AI Brief (X)

More from: Life Sciences

09/05
Carestream Updates DRX LC Detector With AI Noise Reduction
09/05
EClinCloud AI Platform Supports More Than 1,100 Clinical Trials
09/05
Tuya Smart Unveils Doova Home Robot for Seniors at IFA 2026
09/04
ODYSS Unveils N1 AI Necklace for Food Logging
09/04
Withings Adds AI Heart and Lung Sound Analysis to BeamO

Subscribe to Life AI Weekly

Weekly coverage of AI applications in healthcare, drug development, biotechnology research, and genomics breakthroughs.

AI Token Webinar

Whitepaper

Tensordyne Napier: What If One Rack Could Do the Work of Nine?

Tensordyne

This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.

Read more

You May Also Like