The "New Species" of Sports Headphones: The Battle for "The First AI Hardware Entry Point" on Ears

In late August 2026, a lawsuit was filed in the U.S. District Court for the Northern District of California, naming Oura, a leading player in the smart ring industry, as the defendant.

In this lawsuit, the plaintiff cited a research study to challenge Oura's sleep stage recognition capability. At that time, the company had sold a total of about 5.5 million rings, and was reported to be preparing for a public listing at an estimated valuation of about 16 billion U.S. dollars. The controversy quickly spread across social platforms, triggering new public discussions on the accuracy of smart wearable devices.

What is worth noting in this controversy is not only whether a certain indicator of Oura is accurate, but also the long-standing unresolved problem in the entire smart wearable industry exposed by it: devices are already able to collect an increasing amount of data, but still struggle to accurately answer the two most critical questions — what is happening to the user at this moment, and what should be done next second.

Over the past decade, smart watches, bands and rings have continuously added heart rate, blood oxygen, sleep and stress monitoring functions, but in most cases they still form a loop system of recording, analysis and post-review. The device collects data first, the mobile phone generates a report afterwards, and the user finally decides how to adjust. No matter how many data dimensions are added, this relationship is essentially still lagging.

What AI hardware is trying to change is exactly this time lag. It not only needs to record the body, but also understand the physical state while the user is exercising, and give feedback the moment risks or efficiency changes occur.

This means that the competition for smart wearables in the AI era is shifting from recording more data to building a real-time closed loop of perception, decision-making and feedback. At this node where the industry is rediscovering new entry points, the ear, a position that may have been long underestimated, is starting to be recognized by more people.

Founded in 2021, EARWEISS has spent 5 years thinking about and responding to this issue. The company launched the fully customized AI sports headphone Sport Open L in 2026, aiming to transform headphones from audio playback devices into smart terminals that continuously collect human body signals, understand exercise status and provide real-time feedback.

What it points to is not just a functional upgrade of headphone products, but more essentially a potential battle for AI hardware entry points in the smart wearable industry: when AI needs to maintain continuous connection with the human body, why might the ear be a more ideal answer than the wrist and fingers? And with what advantages can AI sports headphones become the first category to successfully run through the closed loop in this round of hardware innovation?

1. Why the Ear: AI Hardware Needs a Complete Closed Loop

Smart wearable devices have been centered around wrists and fingers in the past, mainly driven by usage convenience. Watches and rings have low wearing thresholds, mature user habits, and can accommodate a variety of sensors. But when the product goal is upgraded from daily recording to real-time judgment during exercise, the limitations of these two positions emerge.

During strenuous exercise, the wrist swings with the body, and skin pigment, sweat, wearing tightness and co-frequency vibration generated by movement may all interfere with the photoplethysmography (PPG) signal. Although rings are in closer contact with the skin, they also face the problems of frequent hand movements and large differences in peripheral circulation among different users.

The value of the ear first comes from its physiological structure. The ear area is densely distributed with capillaries, with flat skin and little hair, allowing the sensor to fit more closely and obtain stronger blood flow signals. At the same time, the movement of the ear and the head is relatively synchronized, so the sensor can obtain more stable fixing conditions than the wrist. According to EARWEISS, the PPG signal intensity at the ear can reach about 6 times that at the wrist.

However, stronger signals alone are not enough to support the judgment that the ear is the number one entry point for AI hardware. What truly distinguishes headphones from watches and rings is that they have both input and output capabilities.

Watches and rings are mainly responsible for perception tasks, and complex feedback usually still relies on the mobile phone screen; headphones can collect physiological signals while directly delivering analysis results to users through voice. They are close enough to the human body and occupy the most natural voice channel for human-computer interaction, so they can complete the entire process from collection, understanding, decision-making to feedback in a single device.

This constitutes the core competitive difference between headphones and other smart wearable devices. On this basis, EARWEISS has built a systematic technical solution specifically for ear monitoring through years of R&D accumulation, greatly improving the perception accuracy and data feedback precision of headphones.

Take the CUSTMONITOR 2.0 ear multi-dimensional monitoring technology carried by Sport Open L as an example. It integrates data from green light, red light, infrared PPG and accelerometer sensors to identify and offset noise generated by movement. According to the verification results issued by Beijing Zhongguang Optics Analysis Science and Technology Research Institute, its dynamic heart rate and blood oxygen monitoring accuracy rates reach 98.6% and 98.3% respectively.

The significance of these data is that they technically prove that the signals obtained by headphones already have the foundation to support real-time exercise decision-making. For a device that needs to adjust training rhythm or even issue risk warnings during exercise, accurate perception capability will directly determine the reliability of the suggestions.

Therefore, the answer to the question of why the ear is the entry point for AI hardware is not just that the signal intensity at the tragus is higher. More importantly, the ear meets three conditions at the same time: stable perception, natural interaction and instant feedback, which gives AI hardware the opportunity to form a complete closed loop from understanding the body to influencing behavior for the first time.

2. AI Sports Headphones, a Potential "Phenomenal Application"

A common dilemma faced by AI hardware in the past few years is that its capabilities seem innovative and extensive, but it lacks rigid demand scenarios that users must continuously use.

Many products represented by AI glasses can answer questions, capture images or organize information, but why users need to wear them every day has never been fully addressed.

Sports health is likely to be a scenario where AI wearables can take the lead in landing, because it has three conditions at the same time: high-frequency use, real-time decision-making and clear feedback.

If a person who goes running only sees a heart rate report after finishing the exercise to know whether he ran too fast, whether the cadence is reasonable, and whether his body is close to the risk boundary, in a sense, this data monitoring has lost its value.

Essentially, all these issues are highly time-sensitive. Once the current moment is missed, the value of the information will drop rapidly. In extreme cases, timely acquisition and reminder of relevant information may even prevent users from encountering health crises.

Thus, AI sports headphones have obtained a product logic that traditional health hardware does not have. They do not just record exercise, but participate in the exercise process itself.

For example, AI headphones can personally adjust the exercise rhythm according to the user's heart rate status to guide the user to maintain a proper exercise pace; when the heart rate leaves the target range, it can remind the user to adjust the speed through voice; when the physical state is close to the risk boundary, it can issue a heart rate warning before the user actively notices it.

EARWEISS summarizes this set of capabilities as "perception — understanding — decision-making — feedback". Sport Open L continuously collects heart rate, blood oxygen and exercise status through ear sensors, and then CUSTHEALTH ASSISTANT 2.0 invokes corresponding models according to different exercise scenarios to give instant guidance in the form of voice.

The product can divide the dynamic heart rate state into three intervals: comfortable, controlled and warning. When the indicators cross the preset boundary, the device can directly remind the user through voice. This makes AI sports headphones not only possible to improve training efficiency, but also begin to undertake the function of sports risk management, acting like an AI sports safety guardian to supervise and give real-time feedback throughout the process.

At present, Sport Open L can be maturely applied in 17 types of sports scenarios such as running, cycling and equipment training, completing the sports health closed loop. However, for an AI hardware to become a phenomenal product, algorithm capability alone is not enough. It must solve three practical problems at the same time: whether the data is reliable, whether the feedback is useful, and whether users are willing to wear it for a long time.

The first two problems determine whether the product has value, and the last one determines whether AI can continuously obtain data. In this regard, EARWEISS's solution is personalized "fully customized" features.

Under the full customization mechanism, the headphones fit the user's ear more closely, and the sensor obtains more stable signals; the more comfortable the wearing experience is, the longer the data accumulation period of the device will be, and the more accurate the monitoring effect will be. For an AI system that needs to continuously learn the user's physical state, physical adaptation itself is part of the data and algorithm capabilities.

At present, to get fully customized headphones, users still need to go to the store to collect ear molds, complete 3D modeling and customized design, which to a certain extent raises the usage threshold of the product.

But this also reflects EARWEISS's product philosophy. The EARWEISS team believes that as AI applications accelerate their penetration into daily life, personalized customization will become one of the core trends in the development of AI hardware. In the next few years, the demand for personalized customization of wearable devices such as AR glasses and AI headphones will usher in rapid growth. With the continuous breakthrough of 3D printing and Industry 4.0 technologies, the "last mile" of personalized customization of AI hardware is expected to be opened up faster, and fully customized headphones will gradually move from being a trial choice for a small number of demand-focused users and tech geeks to the broader mainstream consumer market.

Thus, AI sports headphones are likely to open up a path to become a "phenomenal application": they have found a scenario that traditional hardware cannot fully meet, and AI can directly create incremental value. More importantly, users do not need to build new habits to use AI, they only need to wear headphones as they did in the past, and AI can provide real-time value during the use process.

This value is perceptible. It may be a timely reminder to slow down, a cadence adjustment, or a warning issued before risks occur. Compared with general-purpose personal AI assistants with vague scenarios, sports is a scenario with clear goals, timely feedback and verifiable effects, so it is easier to build real user demands.

3. The Future Competition for AI Hardware Entry Points

From smart watches, rings to glasses, the competition among technology companies for AI hardware entry points is essentially to find a connection relationship that can accompany users for a long time and continuously obtain contextual information.

But the connection relationship is not the only criterion. A truly valid AI entry point must also obtain credible data, understand the ongoing context, and influence and optimize user behavior in the least intrusive way.

This is where the particularity of the ear lies. It is not only a relatively stable position for physiological signal collection, but also the most natural voice interaction channel for human beings. The sensors are responsible for monitoring the body, the algorithms are responsible for understanding the body, and the voice sends the decisions back to the users.

Among global tech giants, OpenAI was once rumored to launch its first AI hardware product as AI headphones, and Apple was also reported to have plans to add more AI features to its AirPods series.

In the startup camp, Plaud recently launched AI headphones that integrate recording, transcription, summarization and task execution into audio devices, targeting the segmented demand for meeting and knowledge management; EARWEISS has chosen a route closer to users' daily lives. It is not in a hurry to put a general AI assistant into headphones, but first solves the problems of whether ear physiological signals can be accurately collected, whether exercise status can be understood in real time, and whether the device can be stably worn for a long time.

Behind different routes are different understandings of AI entry points held by different companies. If other companies pay more attention to the application scenarios of continuous dialogue between AI models and users, or the further extension of the existing terminal ecosystem, what EARWEISS hopes to establish at present is the real-time connection between AI and the human body through the ear.

Fully customized headphones are one of the most imaginative and disruptive innovation paths for smart hardware in recent years, which requires reshaping the entire chain of software and hardware R&D, production and manufacturing, and user experience. To this end, the EARWEISS team has spent 5 years and invested over 100 million yuan to build a flexible production line and R&D experimental base. As of August 2026, the company has laid out nearly 180 global patents, including more than 50 invention patents. Therefore, the new experience that EARWEISS can truly bring to the industry is trying to change the relationship between wearable devices and people: headphones can also evolve from players to smart terminals that can drive real-time health decision-making.

So far, the competition scale of AI hardware has changed. The value of entry points in the future will depend on what kind of continuous data an enterprise can obtain, how deeply it can understand the real context, and to what extent it can transform judgments into reliable actions.

This capability will not be obtained only by stronger models. What truly determines the ownership of the entry point is who can establish a real-time connection with real individuals as early as possible, and obtain the qualification to understand people and then influence them. This may be the future that should be envisioned in the final scenario of AI hardware.