Maryland Patent of the Month – January 2026

Patent Provenance and Award Recognition

The subject of this comprehensive analysis is United States Patent No. 12,514,465, titled “Bilateral acoustic sensing for predicting FEV1/FVC.” This seminal intellectual property was applied for on April 8, 2024, and formally awarded on January 6, 2026. The invention, credited to inventors Lloyd Emokpae and Roland N. Pittman, represents a significant leap forward in the field of respiratory diagnostics. In a testament to its innovation and potential, the patent was recently distinguished as the Maryland Patent of the Month. This accolade is particularly notable for its selection methodology; it was not chosen through a traditional manual review but was identified by advanced Artificial Intelligence technology which screened over 1,000 potential patents to isolate the most promising innovation. The AI-driven selection process prioritized patents that demonstrated exceptional novelty, technical advancement, and the capacity for immediate market influence, ultimately selecting Patent 12,514,465 as the preeminent invention in its class.

The selection of Patent 12,514,465 as the Maryland Patent of the Month was driven primarily by its demonstrable real-world impact. In an era where many patents remain theoretical or purely defensive, this invention addresses a critical, unmet need in the management of chronic respiratory diseases, specifically Chronic Obstructive Pulmonary Disease (COPD). The technology’s ability to passively and accurately predict Forced Expiratory Volume in 1 second (FEV1) and Forced Vital Capacity (FVC) using bilateral acoustic sensing positions it as a superior alternative to existing diagnostic modalities. By decoupling lung function monitoring from the physical exertion required by traditional spirometry, the patent offers a solution that is not only technologically superior but also empathetic to the patient experience. Its selection underscores a shift in value assessment towards technologies that can democratize clinical-grade diagnostics, reduce hospital readmissions, and fundamentally improve the quality of life for the millions of patients suffering from debilitating lung conditions.

The Clinical and Pathophysiological Context

To fully appreciate the superiority of the invention described in Patent 12,514,465, one must first understand the clinical landscape it aims to transform. COPD is the third leading cause of death worldwide, claiming over 3 million lives annually. It is a progressive, debilitating condition characterized by airflow limitation that is not fully reversible.

The Limitations of the Current Gold Standard: Spirometry

For decades, the “gold standard” for diagnosing and monitoring COPD has been spirometry. This test requires a patient to inhale maximally and then exhale as forcefully and rapidly as possible into a mouthpiece connected to a flow sensor (pneumotachograph).

• Effort Dependence: The validity of a spirometry test is entirely dependent on the patient’s effort. They must create a tight seal around the mouthpiece and blast air out with maximum force. For elderly patients, or those in the midst of an exacerbation (flare-up), performing this maneuver is often physically impossible or yields sub-optimal, uninterpretable data.
• Intermittency: Spirometry is a “snapshot” in time. It typically occurs during infrequent office visits—perhaps every 3 to 6 months. This leaves massive blind spots in the patient’s longitudinal health record. A patient could be deteriorating for weeks, losing lung function daily, but if their next appointment is a month away, the decline goes unnoticed until it precipitates a crisis.
• Invasiveness and Infection Risk: The maneuver induces coughing and aerosolization of respiratory droplets, posing a significant infection control risk to healthcare providers and other patients, a concern that was starkly highlighted during the COVID-19 pandemic.

The Acoustic Opportunity

The thorax is essentially an acoustic chamber. The lungs, airways, and chest wall form a complex system where sound transmission is dictated by the density and elasticity of the tissue. In a healthy lung, breath sounds have a specific spectral signature. In a COPD patient, pathological changes alter this signature:

• Emphysema: Destruction of alveoli leads to hyperinflation (air trapping). Air is a poor conductor of sound compared to consolidated tissue, leading to “distant” or attenuated breath sounds.
• Chronic Bronchitis: Inflammation and mucus production generate adventitious sounds like wheezes (high-frequency musical sounds caused by narrowed airways) and crackles (discontinuous popping sounds caused by the opening of fluid-filled airways).

Patent 12,514,465 leverages these acoustic principles but adds a critical layer of sophistication: Bilateral Sensing.

Technological Analysis of Patent 12,514,465

The core innovation of Patent 12,514,465 is the system and method for bilateral acoustic sensing to predict spirometric indices without airflow.

Bilateral Architecture

The human respiratory system is paired; we have a right lung and a left lung. However, standard spirometry treats the respiratory system as a single “black box” with one output (the mouth). This masks regional heterogeneity. A patient could have severe mucous plugging in the left lower lobe while the right lung compensates, resulting in a “normal” spirometry reading that hides the developing pathology.

The patent describes a system—implemented in the “WearME” wearable platform—that utilizes sensors placed on both sides of the chest. This bilateral approach allows for:

• Regional Ventilation Analysis: Comparing the acoustic intensity and frequency content between the left and right hemithorax.
• Early Detection of Asymmetry: Conditions like pneumonia, pneumothorax, or localized atelectasis often present unilaterally. The system can detect these discrepancies immediately, serving as an early warning system that global airflow measures would miss.

Sensor Fusion and Machine Learning

The patent does not rely on acoustics alone. It employs a multi-modal sensor fusion approach, integrating:

1. Digital Stethoscopes (Acoustic Sensors): High-fidelity microphones capturing the vibration of air moving through the bronchial tree.
2. Inertial Measurement Units (IMUs): Motion trackers (accelerometers/gyroscopes) that quantify chest wall excursion. This provides a mechanical reference—measuring the physical expansion of the ribcage.
3. ECG and Temperature Sensors: Providing context on cardiac load and systemic infection (fever), which are common comorbidities and triggers for COPD exacerbations.

The “secret sauce” described in the patent is the Machine Learning (ML) algorithm. This algorithm ingests the raw audio and motion data, processes it (likely using techniques like Fast Fourier Transform to analyze spectral power), and maps these features to the standard clinical metrics of FEV1 and FVC.

Accuracy and Validation

The superiority of a medical device is ultimately determined by its accuracy against the reference standard. The data supporting Patent 12,514,465 is compelling. In clinical validation studies involving the WearME device:

• FEV1 Correlation: The system achieved a correlation coefficient () of 0.984 for predicting FEV1 in COPD patients compared to standard spirometry.
• FVC Correlation: The correlation for FVC was even higher at 0.993.
• Diagnostic Agreement: The system showed a Cohen’s kappa of 0.872 for diagnosing spirometric abnormalities, indicating “almost perfect” agreement with hospital-grade equipment.

These numbers are not just statistically significant; they are clinically transformative. They suggest that a passive wearable can provide data virtually indistinguishable from a hospital pulmonary function test.

Comparative Benchmarking and Superiority Analysis

To rigorously assess the superiority of Patent 12,514,465, we must benchmark it against the existing spectrum of respiratory monitoring technologies. The market is currently bifurcated into “Active/Effort-Dependent” devices and “Passive/proxy” devices. The invention described in Patent 12,514,465 bridges this gap, creating a new category of “Passive Quantitative” monitoring.

Competitor 1: Standard Home Spirometers

• Technology: Portable pneumotachographs that require the patient to blow into a tube.
• Comparison:

• Standard: Requires high effort, technique dependent, causes fatigue, spot-check only.
• Patent 12,514,465: Passive (tidal breathing), effort-independent, continuous monitoring.

• Superiority Verdict: The patent is superior because it removes the “user error” and “effort” variables. In elderly COPD populations, the failure rate for performing a correct spirometry maneuver is high. By removing the need for the maneuver, the patent ensures 100% data capture compliance.

Competitor 2: Smart Inhalers (e.g., Propeller Health)

• Technology: Bluetooth add-ons for inhalers that track when and where medication is used. Some advanced versions measure inspiratory flow.
• Comparison:

• Propeller Health: Tracks adherence. It answers the question, “Did the patient take their medicine?” It infers health status based on rescue inhaler usage.
• Patent 12,514,465: Tracks physiology. It answers the question, “Is the patient’s lung function improving?”

• Superiority Verdict: While adherence tracking is useful, it is a proxy. A patient might take their medication perfectly but still deteriorate due to an environmental trigger or infection. The patent provides direct physiological insight (FEV1/FVC) that smart inhalers cannot. It detects the result of the pathology, not just the input of the treatment.

Competitor 3: Other Acoustic/Contact Devices (e.g., Respiri, Stethoscopes)

• Technology: Handheld devices placed on the trachea to record breath sounds (mostly wheeze detection).
• Comparison:

• Competitors: Often unilateral (single point), handheld (requires active use), and qualitative (wheeze yes/no).
• Patent 12,514,465: Bilateral (spatial resolution), wearable (hands-free), and quantitative (liters of air).

• Superiority Verdict: The bilateral nature of the patent is a critical differentiator. Lung disease is rarely uniform. A single-point sensor averages the signal, potentially diluting the sign of a focal problem. Furthermore, the patent’s ability to output numerical FEV1/FVC values allows it to interface directly with existing clinical protocols (which are based on these numbers), whereas “wheeze scores” from competitors require doctors to learn new interpretative frameworks.

Table 1: Comparative Technology Matrix

Real-World Impact and Future Potential

The selection of this patent for the Maryland award was predicated on its “real-world impact.” This impact cascades through the healthcare ecosystem, affecting patients, providers, and payers.

Current Impact: The COPD Crisis

The immediate application of this technology is in the management of COPD.

• Early Exacerbation Detection: COPD exacerbations are the leading cause of hospital admission for these patients. They are often preceded by a “prodromal phase”—a window of 3 to 4 days where subtle physiological changes occur (increased respiratory rate, slight air trapping). The patent’s technology, capable of detecting these changes through acoustic variances, claims to detect flares 48 hours early.
• Intervention Window: This 48-hour head start is the difference between an outpatient prescription for antibiotics/steroids and an ICU admission. By shifting care from the hospital to the home, the technology directly addresses the cost crisis in healthcare.
• Resource Optimization: LASARRUS, the assignee, projects that the WearME system can cut nurse triage time by 50%. Instead of calling every patient to ask, “How do you feel?”, nurses can monitor a dashboard of FEV1 trends and focus only on the patients showing physiological decline.

Economic Implications

• Reimbursement: The device aligns with the expanding CPT codes for Remote Therapeutic Monitoring (RTM) and Remote Patient Monitoring (RPM). This turns the device from a cost center into a revenue generator for practices, incentivizing adoption.
• Value-Based Care: Hospitals are penalized for COPD readmissions. A technology that reduces readmissions is an essential tool for health systems operating under value-based care contracts.

Future Potentials

The technology described in Patent 12,514,465 is a platform, not just a COPD tool.

• Asthma: The validation data showed even higher accuracy in asthma patients (FEV1 ). This could revolutionize pediatric asthma management, where parents often struggle to gauge the severity of their child’s wheezing.
• Post-Acute COVID / Long COVID: Millions of patients are recovering from COVID-19 pneumonia with residual lung scarring. Bilateral acoustic sensing could track the slow resolution of fibrosis or the development of new restrictive patterns without requiring monthly hospital visits.
• Pharmaceutical Clinical Trials: Drug developers spend billions testing new respiratory biologics. Currently, they rely on sporadic spirometry data points. This technology could provide continuous “Real World Evidence” (RWE), allowing trials to demonstrate drug efficacy with smaller sample sizes and higher fidelity data.

R&D Tax Credit Analysis: The Swanson Reed Methodology

The development of the technology underpinning Patent 12,514,465 is a textbook example of the type of innovation the Research and Experimentation (R&D) Tax Credit (IRC Section 41) was designed to support. This federal incentive allows companies to claim a tax credit for a percentage of “Qualified Research Expenses” (QREs).

To successfully claim this credit, a taxpayer must demonstrate that their research activities satisfy the Four-Part Test. Below is a detailed analysis of how a project utilizing Patent 12,514,465 meets these statutory requirements, and how Swanson Reed, a specialist R&D tax advisory firm, can assist in maximizing and defending the claim.

The Four-Part Test Breakdown

Part 1: Permitted Purpose (The “Business Component” Test)

Requirement: The research must intend to create a new or improve an existing “business component.” A business component is defined as any product, process, computer software, technique, formula, or invention to be held for sale, lease, or license, or used by the taxpayer in a trade or business. The improvement must relate to function, performance, reliability, or quality.

Application to Patent 12,514,465:

The project clearly aims to develop a new product—the WearME wearable device—and its associated proprietary software algorithms.

• Functionality: The project creates a new function: the ability to monitor FEV1/FVC bilaterally and passively, which was previously impossible with consumer wearables.
• Performance: The research improved the performance of acoustic monitoring, raising the correlation coefficient from non-diagnostic levels to >0.98, enabling clinical utility.
• Reliability: By integrating IMU motion data with acoustics, the project improved the reliability of the signal in ambulatory settings, filtering out noise that would render other devices useless.

Part 2: Technological in Nature

Requirement: The research must fundamentally rely on the principles of the “hard sciences,” such as engineering, physics, chemistry, biology, or computer science. It does not include research based on soft sciences like economics or psychology.

Application to Patent 12,514,465:

The development of this patent is an interdisciplinary feat of hard science:

• Acoustics & Physics: The core premise relies on the physics of sound propagation through non-homogeneous biological media (lung parenchyma). Understanding how sound waves attenuate through emphysematous vs. healthy tissue is pure physics.
• Electrical & Computer Engineering: Designing the high-fidelity sensor array, minimizing signal-to-noise ratio, and developing the “sensor fusion” circuitry.
• Computer Science (AI/ML): The “AI technology” mentioned in the award selection refers to the sophisticated machine learning models (e.g., neural networks) used to deconvolute the raw acoustic signal into volumetric airflow predictions.
• Biomedical Engineering: The integration of sensors into a “smart glove” or vest form factor requires knowledge of biomechanics and materials science to ensure consistent skin contact without restricting motion.

Part 3: Elimination of Uncertainty

Requirement: At the outset of the project, there must be uncertainty concerning either the capability (can we do it?), the method (how do we do it?), or the appropriate design of the business component. The taxpayer must not know the answer at the start.

Application to Patent 12,514,465:

Significant technical uncertainties existed:

• Capability Uncertainty: “Is it physically possible to predict FEV1 (a mechanical flow metric) solely from acoustic vibrations with clinical accuracy?” Prior to this research, the answer was not definitive.
• Methodological Uncertainty: “What is the optimal algorithm to fuse IMU motion data with acoustic data?” “How do we filter out heart sounds (S1/S2) which overlap in frequency with breath sounds?”
• Design Uncertainty: “Where should the sensors be placed for maximum signal yield? Apical, basal, or mid-axillary?” The patent text and related snippets imply an iterative process to determine the optimal sensor configuration.

Part 4: Process of Experimentation

Requirement: Substantially all (at least 80%) of the research activities must constitute a process of experimentation. This involves identifying the uncertainty, identifying one or more alternatives to eliminate it, and evaluating those alternatives through modeling, simulation, or systematic trial and error.

Application to Patent 12,514,465:

The development pathway demonstrates a rigorous scientific method:

• Hypothesis Generation: Theorizing that bilateral acoustic asymmetry correlates with FEV1 decline.
• Iterative Prototyping: The move from a “smart glove” to the “WearME” vest/strap system indicates a process of testing different form factors to solve issues of sensor coupling and user compliance.
• Validation Studies: The snippets reference clinical trials comparing the device against standard spirometry in 30 volunteers. This is the essence of experimentation—collecting data to verify if the design meets the theoretical goals.
• Refinement: The high correlation achieved (0.984) suggests multiple rounds of algorithm tuning (training and testing phases) to minimize the error delta between the predicted and actual FEV1.

The Role of Swanson Reed

Claiming the R&D credit is a complex compliance exercise. Swanson Reed, as a specialized R&D tax advisory firm, offers a comprehensive methodology to ensure claims are maximized and defensible.

1. Assessment and Scoping:

Swanson Reed would perform an initial feasibility assessment to identify all eligible projects. In this case, they would segregate the “Qualified Research Activities” (algorithm development, sensor engineering, clinical validation) from non-qualified activities (routine market research, aesthetic packaging design).

2. Calculating QREs (Qualified Research Expenses):

The financial benefit is derived from specific expenses. Swanson Reed would help the company aggregate:

• Wages: The taxable wages of inventors like Lloyd Emokpae and Roland Pittman, as well as software engineers and data scientists, for the portion of time spent on the experimentation.
• Supplies: The cost of prototypes, sensors, circuit boards, and fabrication materials consumed during the R&D process.
• Contract Research: 65% of amounts paid to third parties (e.g., university labs, testing facilities) to conduct research on the company’s behalf.
• Cloud Computing: Costs for cloud-based servers (AWS/Azure) used to train the resource-intensive AI models.

3. Documentation Strategy: The IRS requires contemporaneous documentation. Swanson Reed employs a “specifically engineered documentation methodology” to build an audit-ready file. This would include:

• Nexus Creation: Linking every dollar claimed to a specific technical uncertainty and experimental activity.
• Technical Narratives: Writing detailed descriptions of the “hard science” challenges (e.g., “The challenge of acoustic impedance matching…”).
• Evidence Compilation: Gathering lab notebooks, Git commit histories, test logs, and the patent application itself as proof of the “Process of Experimentation.”

4. Audit Defense (CreditARMOR): Should the IRS audit the claim, Swanson Reed provides CreditARMOR, an AI-driven audit risk assessment and defense platform. They would leverage the Maryland Patent of the Month award as external validation of the technology’s novelty, helping to rebut any IRS assertion that the work was “routine engineering.” Their deep expertise in the 4-part test ensures that the “Elimination of Uncertainty” argument is robustly articulated, protecting the company’s financial interests.

Table 2: R&D Tax Credit Eligibility Matrix for Patent 12,514,465

Final Thoughts

United States Patent 12,514,465 stands as a paragon of modern medical innovation. By fusing bilateral acoustic physics with advanced artificial intelligence, it transforms the human body’s natural sounds into precise, actionable clinical data. Its recognition as the Maryland Patent of the Month—selected by AI for its real-world impact—confirms its status not just as a legal asset, but as a humanitarian tool capable of saving lives and healthcare dollars.

The technology’s superiority lies in its ability to be both passive and precise, offering a “set and forget” solution that captures the nuanced physiological reality of COPD that current competitors miss. For the innovators behind this breakthrough, the R&D Tax Credit offers a vital mechanism to reinvest in this life-saving work. Through the rigorous application of the Four-Part Test and the expert guidance of firms like Swanson Reed, the financial risks of such ambitious R&D can be mitigated, ensuring that the journey from patent to patient is both sustainable and successful.