MySleepart Files IPO Prospectus: Pioneering AI-Driven Smart Sleep System for Automated Intervention and Sleep Disorder Screening
The global sleep medicine market comprises products and services. According to the report "2017 International Comparison, Market Demand, and Supply Analysis of China's Medical Industry" by China Industrial Information, the size of the sleep medicine market reached $254.09 billion in 2015. Of this, products accounted for 88% of the overall market, while services accounted for 12%. Currently, the global treatment of insomnia remains primarily at the stage of using synthetic sedatives and hypnotics. Due to the propensity of these medications to cause drug tolerance, addiction, and withdrawal reactions, as well as their inherent adverse effects, seeking non-pharmacological solutions for insomnia has become a highly significant topic in academic circles.
MySleepart is a technology company that integrates intelligent products and services to provide sleep solutions for individuals with sleep disorders. Centered on a matrix of comprehensive smart sleep-aid products, MySleepart has built a closed-loop data service ecosystem for actionable health management. Beyond its product offerings, MySleepart has developed an AI-powered big data health information system for sleep analysis. In collaboration with physician groups, the system delivers professional sleep health solutions and provides users with personalized sleep health guidance.
Sleep technology products on the market primarily address two major issues. The first is poor sleep quality. In early 2017, Huawei’s Sports Health division released the “Report on Sleep Quality in China,” which revealed that the sleep quality of Chinese residents was a cause for concern, with an average sleep duration of less than seven hours and 64% of survey respondents considering themselves sleep-deprived. The second issue pertains to health problems latent during sleep, such as sleep apnea syndrome (SAS). Although these sleep disorders are chronic and stubborn, they are manageable, thereby creating certain market opportunities for intervention by smart products.
In addressing poor sleep, the MySleepart smart bed system builds upon an electric bed base integrated with sensors to capture physiological data—such as heart rate, respiratory rate, body movements, and snoring—as well as environmental data including bedroom temperature, humidity, and air quality. The system stores this data in the cloud, where backend artificial intelligence algorithms analyze the user’s sleep status and quality in real time. Based on these insights, the backend can automatically adjust the bed’s posture to extend the user’s deep sleep duration.
In terms of snoring intervention, MySleepart’s snore monitor utilizes neural network algorithms to identify snoring sounds. The cloud platform automatically adjusts the posture of the smart bed based on feedback from snoring data, physically reducing the frequency of snoring episodes through a system-linked intervention approach.
Addressing potential health issues during sleep imposes higher requirements on products. These products must not only capture patients’ physiological data but also align with established diagnostic criteria to facilitate disease diagnosis based on such data.
To enable initial screening and intervention for sleep disorders while ensuring the product’s medical-grade attributes, MySleepart has launched a sleep monitoring blanket. Its core technology utilizes piezoelectric film sensors to capture ballistocardiography (BCG) signals without the need for wearable devices, employing micro-movement monitoring to calculate heart rate, respiratory rate, and sleep quality.
To ensure the product’s medical attributes and achieve medical-grade application standards, MySleepart has added snoring monitoring and blood oxygen monitoring modules to its sleep monitoring mat. Centered on MySleepart’s proprietary neural network module, the sleep monitoring mat performs initial screening for sleep apnea by integrating and analyzing monitored respiratory waves, blood oxygen data, and heart rate variability.
Gao Xin, co-founder of MySleepart, told VCBeat, “We aim to bring sleep disorder monitoring products from hospitals into homes through a lightweight wearable approach. Given that the data reliability of current consumer-grade products remains questionable, we intend to develop a medical-grade sleep monitoring device to facilitate initial screening and health management for individuals with symptoms of sleep apnea.”
In terms of its business model, MySleepart chooses to accumulate resources from the B-end first, and then promote them to the C-end. Currently, MySleepart is mainly exploring the market in nursing homes, providing health management and monitoring for the elderly with huge health management needs.
For MySleepart, expanding into the B2B market is a process of market education. More importantly, MySleepart can collect customer characteristic data to train algorithmic models, thereby securing greater influence in niche markets. To deliver valuable health reports and solutions, the product requires access to sufficient data. However, data volume alone is not decisive; rather, it is essential to obtain accurate data targeted at specific demographic segments.
Gao Xin explained, “We conduct data collection in a targeted manner, as our R&D process has revealed that sleep characteristics vary across different age groups, genders, and geographic regions. At our Beijing R&D center, we primarily collaborate with the Chinese PLA General Hospital (301 Hospital) and Peking University Third Hospital to continuously acquire clinical data from individuals with sleep disorders. In the broader consumer market, we are integrating sleep data with health metrics for the elderly. Other initiatives include collecting female-specific data, with future plans to combine sleep insights with beauty and skincare applications. Overall, through B2B channels, we integrate the collection and analysis of sleep data with specific industry scenarios.”
MySleepart’s current team of 12 includes eight R&D engineers. Co-founder and CTO, Luan Sheng, is a postdoctoral fellow in Computer Science from Beihang University. He has nearly a decade of R&D experience in physiological parameter acquisition and algorithms, and has led or participated in multiple national-level projects on service robots, including the Major R&D Special Project undertaken by the company in 2018 under the Ministry of Science and Technology.
Currently, the company is seeking Pre-A round financing. This round aims to raise RMB 8 million for channel development, optimization of the sleep data platform, product research and development, and team expansion. Previously, the company had secured RMB 2 million in angel financing and RMB 4 million in venture capital.