Jilin University Licenses Innovative Respiratory Monitoring Patent to Changchun Chengshi Health Industry Co., Ltd. under Revenue-Sharing Model

Recently, the Scientific Research Institute of Jilin University released a public notice on the transformation of scientific and technological achievements, stating that the university intends to grant an exclusive license for its owned“Device and Method for Monitoring Respiratory Continuity and Breath Sounds”Patent rights licensed to Changchun Chengshi Health Industry Co., Ltd., license term10 Years, the contract value is determined byRevenue-sharing model based on a percentage of the product’s ex-factory price. The person in charge and core inventor of this licensing project is from the Second Clinical Medical College of Jilin UniversityDr. Sun Xufang and Her Team。

The patent technology proposed for transfer in this instance innovativelyIntegration of Acoustic and Temperature Sensors into the Anesthesia Breathing Circuit, by acquiring, transmitting, and analyzing respiratory sounds and airflow data in real time, this system achieves automatic monitoring of breathing continuity and abnormal respiratory sounds in patients under controlled ventilation, along with immediate alerts. This technology aims to eliminate delays in assessing respiratory status, significantly enhancing the sensitivity, timeliness, and safety of mechanical ventilation management, featuring precision and dual-redundancy safeguards.

Controlled ventilation refers to a life-support measure involving artificial respiration that is established when a patient loses the ability to breathe spontaneously or during general anesthesia for surgical procedures. Its implementation relies on a sophisticated mechanical process:First, perform endotracheal intubation by inserting a tube through the patient’s mouth into the trachea; the cuff at the distal end of the tube is then inflated to create a seal against the tracheal wall.

The distal end of the catheter is tightly connected to the gas circuit of an anesthesia machine or ventilator. When the machine is activated, it delivers a flow of gas with an appropriate oxygen concentration into the patient’s lungs under positive pressure, causing alveolar expansion and completing the artificial “inspiratory phase.” This mechanism differs from the principle of spontaneous human breathing, which relies on negative intrathoracic pressure to draw air into the lungs.

Subsequently, during the "expiratory phase," the machine stops delivering gas, and pulmonary gases are passively expelled by relying on the elastic recoil of the thoracic cage and lung tissue until the intrapulmonary pressure equilibrates with atmospheric pressure. The anesthesiologist needs to preset key parameters on the device, such as tidal volume, respiratory rate, inspiratory-to-expiratory ratio, and peak airway pressure limit; the entire controlled ventilation process then cycles repeatedly based on these settings.

To ensure the safety and efficacy of controlled ventilation, current clinical monitoring protocols primarily focus on two key aspects.

The first aspect is the indirect monitoring of patients' key vital signs.Among them,End-Tidal Carbon Dioxide Pressure Monitoringis a core technology. Its principle is based on the property that carbon dioxide gas absorbs infrared light at specific wavelengths. By analyzing the absorption rate of infrared light by exhaled gas, it calculates the end-tidal carbon dioxide concentration, thereby generating a waveform and calculating the respiratory rate. This waveform reflects the periodicity of respiration; however, the absolute concentration value does not directly indicate airway patency. Mechanical issues such as catheter kinking or secretion obstruction may be present.

Another widely used technology is transcutaneous pulse oximetry monitoring.It non-invasively estimates arterial oxygen saturation by shining light through sites such as the fingertip via sensors, leveraging the differential absorption rates of red and infrared light by oxyhemoglobin and deoxyhemoglobin in the blood. However, blood oxygen saturation reflects one of the final outcomes of respiration, rather than providing direct monitoring of the respiratory process itself. The causes of its decline are extremely complex, including heart failure, pulmonary infections, severe shock, anemia, and even improper sensor placement; respiratory arrest is merely one of many potential causes. Therefore, when an alarm for decreased blood oxygen saturation is triggered, healthcare professionals require considerable time to troubleshoot and cannot immediately pinpoint respiratory issues.

More critically, there is a fatal time delay between the cessation of breathing and the significant drop in blood oxygen saturation to the typical alarm threshold of 90%. Furthermore, the alarm tones of conventional monitors lack sufficient alertness in noisy operating room environments. This renders reliance on such monitoring subject to major drawbacks, including lag, non-specificity, and low sensitivity.

Furthermore, there are methods that estimate respiratory rate by measuring changes in thoracic electrical impedance via ECG electrodes; however, the resulting values are susceptible to interference from factors such as electrode placement and patient respiratory amplitude, thereby limiting their reliability.

The second aspect of monitoring directly targets the operational parameters of the anesthesia machine or ventilator itself., such as tidal volume, respiratory rate, and airway pressure.These parameters are measured and displayed in real time by various high-precision sensors built into the machine, such as differential pressure sensors, turbine or ultrasonic flow sensors.

Although these data directly reflect whether the machine is delivering gas normally, they essentially monitor the operational status of the “machine” rather than the physiological response of the “patient.” The machine may deliver gas normally, but whether the gas effectively reaches the patient’s alveoli, and whether there is partial airway obstruction or leakage, cannot be directly and immediately determined based solely on these parameters.

In summary, all existing monitoring systems share a common fundamental flaw: they allLack of Direct, Continuous Monitoring and Analysis of Patient Breath Sounds. Breath sounds are noises generated when gas flows through the respiratory tract; their characteristics directly reflect airway patency, continuity of gas flow, and effectiveness of ventilation.

The lag, indirectness, and weak alerting capability of current technologies result in delayed detection of sudden, persistent respiratory interruptions or airway obstruction during controlled ventilation, providing insufficient urgency in alerts to healthcare providers and potentially threatening patient safety. Therefore, there is an urgent clinical need for a reliable indicator that can directly and real-time monitor breath sounds and correlate them with respiratory continuity.

The core advantages and advanced nature of the monitoring scheme proposed in this patent lie in its creativeDirect, simultaneous, and continuous monitoring of breath sounds and respiratory airflow temperature has been introduced, thereby establishing a real-time early warning system with dual safeguards., fundamentally transforming the traditional model of respiratory monitoring that relies on indirect and lagging parameters.

Specifically, the device achieves this throughPrecision-designed sensor layout and signal processing circuits to achieve this goal. At the connection between the patient's endotracheal tube and the anesthesia machine circuit, assembled side by side areElectret Microphone Sound Sensor and Fast-Response Negative Temperature Coefficient (NTC) Thermistor Temperature Sensor. An electret microphone is an acoustic-to-electric transducer that utilizes a permanently polarized dielectric to generate charge, capable of capturing with high fidelity the subtle sounds produced by airflow through the airways.

These raw physical signals of breath sounds are amplified, filtered, and level-adjusted by dedicated acoustic measurement circuits, converting them into analog electrical signals suitable for microcontroller analysis. Meanwhile, the resistance of the thermistor changes rapidly in response to variations in the temperature of the contacting respiratory airflow; this change is captured by a high-precision temperature measurement circuit. Employing a bridge design with differential amplification, this circuit amplifies weak temperature difference signals and converts them into single-ended voltage signals via a unique adder circuit for reading by the analog-to-digital converter.

The processing and analysis of data reflect the intelligence and precision of this solution. The device adoptsDual-CPU ArchitecturePerform collaborative computing. The second CPU is dedicated to the high-frequency acquisition and preliminary processing of these two sensor signal channels. For audio signals, it employs the Fast Fourier Transform (FFT) algorithm to conduct real-time spectral analysis.

This not only calculates the intensity of breath sounds but also analyzes their frequency components, thereby laying the foundation for identifying abnormal breath sounds. For temperature signals, it precisely times each cycle consisting of warming during exhalation and cooling during inhalation. All these preprocessed cyclic data are transmitted in real time to the primary CPU, which serves as the core of the system.

The first CPU executes the core decision-making algorithm based on the received data stream. In terms of continuous respiratory monitoring, it makes determinations by simultaneously relying on two independent physical phenomena.1. Analyze the rhythmicity of respiratory sound signals.Normal controlled breathing produces a steady rhythm of alternating inspiratory and expiratory sounds; once this rhythm is lost, the system can determine that continuous breathing may be interrupted.Second, analyze the periodic fluctuations of the respiratory airflow temperature curve.

Since the temperature of exhaled gas is typically higher than that of the inhaled gas from the anesthesia machine, the temperature measured at the airway interface exhibits regular, periodic fluctuations. Once the respiratory gas supply is interrupted, these rhythmic temperature variations immediately transition into a monotonic change and eventually stabilize at a constant level. By employing fast-response thermistors, this system can detect the loss of such rhythmic patterns within a single respiratory cycle (as short as 5 seconds), offering a response speed far superior to the minute-level delay associated with relying on decreases in blood oxygen saturation.

In the realm of airway patency monitoring, this protocol has achieved a revolutionary breakthrough. It accomplishes this byContinual Learning and Recognition of Spectral Features in Respiratory Audio, capable of automatically identifying abnormal breath sounds. For example, crackles may be produced when there are secretions in the airways, while wheezing or stridor may occur during bronchospasm.

Once the system detects these characteristic abnormal spectral patterns, it immediately triggers an alarm to alert healthcare providers of decreased airway patency. This effectively equips patients with a tireless “electronic stethoscope,” enabling continuous auscultation of airway status and filling the gap in clinical real-time monitoring of this critical indicator.

Furthermore, the advanced nature of this protocol is also reflected in itsRich Derivative Monitoring CapabilitiesBased on precise measurements of the expiratory and inspiratory times for each breath, the system can directly calculate the real-time respiratory rate.

More importantly, since there is a proportional relationship between the volume of gas exchanged during respiration and the magnitude of temperature change, the system incorporates ambient temperature parameters into its established mathematical model to accurately estimate the patient’s tidal volume—a key ventilation parameter—thereby providing an additional dimension for monitoring.

In summary, the advantages of this patented technology are primarily reflected inDirect, Real-Time, Dual-Channel Verification and Intelligent Analysis。

It shifts the monitoring focus from “machine output” and “indirect physiological outcomes” to the “physical phenomena of the patient’s airway itself,” establishing a sensitive and reliable safety barrier by leveraging the two most direct indicators: breath sounds and airflow temperature. Its unique dual-criterion design (acoustic pattern + thermal pattern) significantly enhances alarm accuracy and anti-interference capability, while its automatic recognition of abnormal breath sounds pioneers continuous quantitative monitoring of intraoperative airway patency, substantially improving the safety of controlled ventilation and the precision of clinical management.

In response to systemic challenges in perioperative patient vital signs monitoring—such as data silos, delayed alerts, and heavy reliance on clinicians’ experiential judgment—leading medical technology companies and research institutions worldwide are racing to develop next-generation monitoring systems characterized by multimodal data fusion, with the aim of enabling proactive prediction and precise intervention in patients’ physiological status.

In the international market,Masimo Corporation’s core technology platform is groundbreakingMasimo Signal Extraction Technology (SET®)This technology effectively overcomes the limitations of traditional pulse oximeters during patient motion and low-perfusion states, providing more reliable monitoring for clinical practice. Building on this foundation, Masimo has developed a diversified product portfolio that includes rainbow® Pulse CO-Oximetry technology, acoustic respiratory monitoring, capnography, and SedLine® brain function monitoring, which are widely used in various clinical settings such as operating rooms, intensive care units, emergency departments, and general wards.

In the field of respiratory monitoring, Masimo offers two core complementary technological solutions. The first isEnd-Tidal Carbon Dioxide (EtCO₂) Monitoring, this technology is primarily delivered through devices such as Radius Capnography™. Its mechanism of action is based on mainstream infrared spectroscopy, which directly measures the carbon dioxide concentration in the patient’s end-tidal exhaled gas flow, providing quantitative EtCO₂ values and continuous capnography waveforms. This not only enables precise monitoring of ventilation adequacy but also allows clinicians to early identify critical conditions such as endotracheal tube displacement and airway obstruction through changes in waveform morphology. As a mature clinical monitoring modality, this technology has been integrated into the Root® patient monitoring platform and has received extensive certifications, including the CE mark, for routine use worldwide.

Another key technology isAcoustic Respiratory Monitoring(Rainbow Acoustic Monitoring™, RAM), which represents a different monitoring pathway. First introduced in 2009, this technology is the world’s first to enable non-invasive, continuous acoustic respiratory rate monitoring. Its specific mechanism involves attaching an innovative adhesive sensor (such as the RAS-45) near the patient’s trachea on the neck to capture breath sounds. The acquired acoustic signals are then processed using Masimo’s proprietary SET® signal extraction technology, which isolates and extracts respiration-related characteristic signals from potential environmental noise and other physiological noises, ultimately calculating the continuous Acoustic Respiratory Rate (RRa™) and potentially displaying the acoustic waveform.

This monitoring modality is particularly critical for patients receiving opioid analgesia or under sedation in the postoperative period, as it can provide earlier indication of respiratory depression or apnea events than reliance on desaturation of blood oxygen levels. The technology has also reached maturity; its dedicated sensors have obtained CE marking and, as an integral component of the Masimo rainbow® technology platform, are deployed in hospitals worldwide.

In China,Yu Shin Medical Device Technology Co., Ltd.(Heroic Faith Medical Science Co., Ltd.) is a medical technology startup focused on developing AI-driven continuous respiratory monitoring solutions, with its core product being an integrated hardware and software“AIRMOD System™” Clinical Respiratory Physiology Monitoring System。

This system comprises the “Zhengyin Electronic Stethoscope” (also known as the AccurSound 101 Electronic Stethoscope) and the “Airmod Respiratory Spectrum Display Software.” The system operates as follows: first, it continuously and non-invasively collects patients’ respiratory sounds using noise-canceling electronic stethoscope patches; subsequently, these audio signals are transmitted to the Airmod software, which performs real-time analysis using an artificial intelligence algorithm trained on a foundational dataset of over 1.6 million clinically annotated respiratory sound records.

AI is capable not only of calculating respiratory rate but also of identifying and visualizing the periodic rhythm of breathing. Furthermore, it can detect abnormal breath sounds, such as wheezing and rhonchi, which may indicate airway obstruction. This enables healthcare professionals to both “hear” and “see” respiratory status, allowing for earlier identification of risks such as apnea or airway compromise before vital signs deteriorate, including declines in blood oxygen saturation. The product is primarily designed for continuous respiratory monitoring during non-intubated anesthesia sedation (moderate sedation) in operating rooms and intensive care units.

Currently, the product has entered the market application phase. Its software, “Airmod,” received FDA 510(k) clearance for Class II medical devices from the U.S. Food and Drug Administration (FDA) in April 2025. Meanwhile, the Zhengyin electronic stethoscope has long been certified by the Taiwan Food and Drug Administration (TFDA) and has established clinical collaborations and applications in multiple medical centers across the United States and Taiwan.

Looking ahead, the evolution of respiratory monitoring will likely extend beyond the precise measurement of single parameters, deepening instead toward multimodal data fusion and intelligent early warning systems. Meanwhile, monitoring scenarios are expanding from core settings such as operating rooms and intensive care units (ICUs) to general wards, postoperative recovery, and even remote home management, imposing new requirements for device miniaturization, wireless connectivity, and interoperability.

Therefore, the core of future competition will lie in how to capture patients’ physiological deterioration signals earlier and more accurately, and integrate discrete monitoring data into valuable clinical decision support, thereby truly establishing a proactive and continuous patient safety defense line.