DCT

2:23-cv-00553

Research Foundation for State University Of New York v. Huawei Device Co Ltd

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I. Executive Summary and Procedural Information

  • Parties & Counsel:
  • Case Identification: 2:23-cv-00553, E.D. Tex., 11/22/2023
  • Venue Allegations: Plaintiffs allege venue is proper in the Eastern District of Texas because Defendant, a foreign corporation, conducts substantial business in the district through authorized retailers and distributors, derives revenue from infringing acts within the district, and places the accused products into the stream of commerce with awareness of their sale and use in Texas.
  • Core Dispute: Plaintiffs allege that Defendant’s smartwatches and associated health monitoring applications infringe seven patents related to algorithms for monitoring physiological functions, such as detecting cardiac arrhythmias and processing biometric sensor data to remove motion artifacts.
  • Technical Context: The technology concerns algorithms used in wearable devices like smartwatches to analyze physiological data, a key feature in the rapidly growing multi-billion dollar consumer market for health and fitness monitoring.
  • Key Procedural History: The complaint does not mention any prior litigation, Inter Partes Review (IPR) proceedings, or licensing history related to the patents-in-suit.

Case Timeline

Date Event
2007-08-02 ’326 Patent Priority Date
2011-01-21 ’428 Patent Priority Date
2013-04-09 ’326 Patent Issued
2013-05-01 ’576 Patent Priority Date
2014-05-01 ’921 and ’601 Patents Priority Date
2015-01-29 ’362 Patent Priority Date
2015-06-09 ’647 Patent Priority Date
2016-08-09 ’576 Patent Issued
2017-07-25 ’428 Patent Issued
2018-06-05 ’921 Patent Issued
2019-05-07 ’647 Patent Issued
2019-05-14 ’601 Patent Issued
2020-05-19 ’362 Patent Issued
2023-11-22 Complaint Filing Date

II. Technology and Patent(s)-in-Suit Analysis

U.S. Patent No. 8,417,326 - “RR Interval Monitoring Method and Blood Pressure Cuff Utilizing Same”

The Invention Explained

  • Problem Addressed: The complaint alleges the invention addresses the prior art's limitation of requiring large databases of "training data" to accurately detect Atrial Fibrillation (AF) (Compl. ¶33).
  • The Patented Solution: The invention provides a method for real-time AF detection that combines multiple statistical techniques without needing prior training data (Compl. ¶33). This is achieved by analyzing a sequence of heart beat intervals and calculating three specific metrics: Turning Points Ratio (TPR) to test for randomness, Root Mean Square of Successive Differences (RMSSD) to quantify variability, and Shannon Entropy (SE) to characterize complexity (’326 Patent, col. 4:51-67).
  • Technical Importance: This approach allows for higher accuracy in AF detection without the significant overhead and potential limitations of systems reliant on large, pre-existing datasets (Compl. ¶33).

Key Claims at a Glance

  • The complaint asserts at least independent Claim 1 (Compl. ¶95).
  • Claim 1 recites an AF analysis method comprising the essential elements of:
    • obtaining an output that includes a heart beat;
    • deriving a heart beat interval;
    • analyzing a number (N) of heart beat intervals from the output; and
    • detecting a likelihood of AF by calculating a Turning Points Ratio (TPR), a root mean square of successive (RMSSD) heart beat intervals, and calculating Shannon Entropy (SE) of the N heart beat intervals.
  • The complaint reserves the right to assert additional claims (Compl. ¶112).

U.S. Patent No. 9,408,576 - “Detection and Monitoring of Atrial Fibrillation”

The Invention Explained

  • Problem Addressed: The patent addresses the problem of inaccurate AF detection algorithms that can be distorted by, or fail to discriminate between, other forms of arrhythmia such as premature ventricular contractions (PVC) and premature atrial contractions (PACs) (Compl. ¶¶39, 42).
  • The Patented Solution: The invention discloses a computer-implemented method that discriminates between AF and other arrhythmias by first constructing a "Poincare plot" of time interval data from a subject's heart rate signal (’576 Patent, col. 19:50-59). The method then identifies and subtracts data patterns corresponding to specific arrhythmias like bigeminy or trigeminy, creating "updated data" that is subsequently analyzed using statistical metrics to determine if the subject has AF or a normal sinus rhythm with PACs/PVCs (Compl. ¶119).
  • Technical Importance: This method provides a more efficient and realizable real-time technique for not only detecting AF but also distinguishing it from other common arrhythmias, thereby potentially reducing false positives (Compl. ¶42, 131).

Key Claims at a Glance

  • The complaint asserts at least independent Claim 1 (Compl. ¶115).
  • Claim 1 recites a computer-implemented method for discriminating between AF and PVC/PACs comprising the essential elements of:
    • demarcating boundaries in a Poincare plot space;
    • constructing a Poincare plot of time interval data from a subject under test;
    • identifying data patterns in the plot corresponding to bigeminy, trigemini, and quadragemini indicating PAC or PVC;
    • obtaining updated data by subtracting the identified pattern data from the time interval data;
    • obtaining a root mean squared of successive differences, a Shannon entropy, and a turning point ratio for the updated data; and
    • comparing these metrics to predetermined thresholds to determine if the subject has AF or normal sinus rhythm with PVC or PAC.
  • The complaint reserves the right to assert additional claims (Compl. ¶139).

U.S. Patent No. 9,713,428 - “Physiological Parameter Monitoring with a Mobile Communication Device”

  • Technology Synopsis: The patent is directed to systems for physiological monitoring with a mobile device that can detect and account for motion artifacts to ensure the quality of reported results (Compl. ¶48). The method involves analyzing a physiological signal, calculating an indicator of volatility like Shannon entropy, and deciding whether to retain the measurements based on a comparison to a threshold, thereby filtering out data corrupted by motion (Compl. ¶146).
  • Asserted Claims: At least Claim 1 (Compl. ¶142).
  • Accused Features: The accused smartwatches allegedly use algorithms to perform physiological monitoring and detect motion artifacts to ensure acceptable quality of the results (Compl. ¶¶147, 153).

U.S. Patent No. 9,986,921 - “Detection and Monitoring of Atrial Fibrillation”

  • Technology Synopsis: The patent describes a real-time arrhythmia discrimination method for smartphones that can distinguish between normal sinus rhythm (NSR), AF, PACs, and PVCs (Compl. ¶57). It overcomes the limitation of inaccurate AF detection when many PAC/PVC episodes are present, which can mimic the random dynamics of AF (Compl. ¶60). The method involves obtaining and comparing statistical metrics (root mean squared of successive differences, Shannon entropy, turning point ratio) for peak-to-peak interval data to predetermined thresholds (Compl. ¶168).
  • Asserted Claims: At least Claim 1 (Compl. ¶164).
  • Accused Features: The accused smartwatches are alleged to implement a method for discriminating between various arrhythmias using pulsatile time series data (Compl. ¶¶169, 172).

U.S. Patent No. 10,278,647 - “Method and Apparatus for Removing Motion Artifacts from Biomedical Signals”

  • Technology Synopsis: The patent is directed to a method for reconstructing a heart-related signal that is corrupted with motion artifacts (Compl. ¶66). It uses a time-varying spectral analysis of both the heart-related signal (e.g., from a PPG sensor) and a motion signal (from a motion sensor) to suppress the motion artifacts and reconstruct a cleaner heart-related signal (Compl. ¶¶69, 187).
  • Asserted Claims: At least Claim 1 (Compl. ¶183).
  • Accused Features: The accused smartwatches allegedly use an algorithm to reconstruct a heart-related signal from a biomedical sensor by employing a time-varying spectral analysis of both the heart signal and a motion signal to account for motion artifacts (Compl. ¶¶188, 189).

U.S. Patent No. 10,285,601 - “Detection and Monitoring of Atrial Fibrillation”

  • Technology Synopsis: This patent, related to the ’921 patent, describes a system for real-time arrhythmia discrimination that can distinguish between NSR, AF, PACs, and PVCs using pulsatile time series from a device like a smartphone (Compl. ¶75). The system is configured to obtain statistical metrics for peak-to-peak interval data and compare them to thresholds to determine if a subject has normal sinus rhythm without PAC or PVC (Compl. ¶205).
  • Asserted Claims: At least Claim 1 (Compl. ¶201).
  • Accused Features: The accused smartwatches allegedly contain one or more processors configured to execute an algorithm that discriminates between various arrhythmias using pulsatile time series data (Compl. ¶¶206, 213).

U.S. Patent No. 10,653,362 - “Motion and Noise Artifact Detection and Reconstruction Algorithms for Photoplethysmogram and Equivalent Signals”

  • Technology Synopsis: The patent discloses a method for physiological monitoring using a PPG signal that includes a motion and noise artifact detection algorithm (Compl. ¶84). The method computes a "noise quality index" from a time-frequency spectrum of the signal, which is then used in a statistical learning method to determine if the signal segment is corrupted by motion artifacts before it is used to determine a physiological parameter (Compl. ¶¶87, 228).
  • Asserted Claims: At least Claim 1 (Compl. ¶224).
  • Accused Features: The accused smartwatches allegedly implement a method for monitoring physiological parameters from a PPG signal that includes obtaining a noise quality index from a time-frequency spectrum to determine if the signal is corrupted by motion artifacts (Compl. ¶¶229, 231, 241).

III. The Accused Instrumentality

Product Identification

  • The accused products are numerous models of Huawei smartwatches and fitness bands, including the Huawei Watch 4 Series, Huawei Watch Ultimate, Huawei Watch GT series, Huawei Watch FIT series, and Huawei Band 7 and 8, collectively referred to as the "Accused Watches" (Compl. ¶95).

Functionality and Market Context

  • The Accused Watches are alleged to be physiological monitoring devices that track key health indicators including heart rate and SpO2 levels (Compl. ¶¶6, 91). They incorporate technology branded as "HUAWEI TruSeen™ 5.0+," which uses photoplethysmographic sensors in a ring formation with multiple light sources to monitor the user's heart rate (Compl. p. 20). A marketing image shows the sensor array on the back of a watch case designed to curve around the wrist (Compl. p. 20).
  • Data from the watches is presented to the user through the watch interface and via graphs of long-term trends in the "Huawei Health app" (Compl. ¶92). The complaint alleges these devices offer "cutting edge health-related features" to compete in the growing consumer smartwatch market (Compl. ¶19). A screenshot of the Huawei Health app shows an interface for downloading the application to a smartphone (Compl. p. 25).

IV. Analysis of Infringement Allegations

’326 Patent Infringement Allegations

Claim Element (from Independent Claim 1) Alleged Infringing Functionality Complaint Citation Patent Citation
An Atrial Fibrillation (AF) analysis method comprising: obtaining an output that includes a heart beat; The Accused Watches' algorithm obtains an output that includes a heart beat via photoplethysmographic sensors. A product image shows the watch face displaying a heart rate of 82 bpm (Compl. p. 21). ¶101 col. 2:1-2
deriving a heart beat interval; The algorithm used by the Accused Watches allegedly derives a heart beat interval from the heart beat output. ¶102 col. 2:1-2
analyzing a number (N) of heart beat intervals from the output; The algorithm allegedly analyzes a number of these derived heart beat intervals. The Huawei Health app is alleged to display graphs of health trends (Compl. p. 22). ¶103 col. 4:51-53
and detecting a likelihood of AF by: calculating a Turning Points Ratio (TPR) of the N heart beat intervals; calculating a root mean square of successive (RMSSD) heart beat intervals; and calculating Shannon Entropy (SE) of the N heart beat intervals. The complaint alleges on information and belief that the algorithm used by the Accused Watches performs these three specific calculations to detect a likelihood of AF. ¶104 col. 4:51-67
  • Identified Points of Contention:
    • Evidentiary Question: The complaint's allegations that the Accused Watches perform the specific calculations of TPR, RMSSD, and SE are made "on information and belief" (Compl. ¶104). This raises the evidentiary question of what proof Plaintiffs will offer to show that the accused algorithm performs these three distinct statistical analyses as claimed, rather than a different or more general method for AF detection.
    • Scope Question: The claim recites deriving a "heart beat interval." The Accused Watches use PPG sensors, which measure blood volume changes. This raises the question of whether the "heart beat interval" derived from a PPG signal is the same as the "RR interval" primarily discussed in the patent's detailed description (’326 Patent, col. 4:51-53), which is typically derived from an ECG signal.

’576 Patent Infringement Allegations

Claim Element (from Independent Claim 1) Alleged Infringing Functionality Complaint Citation Patent Citation
A computer implemented method for discriminating between atrial fibrillation and premature ventricular contractions (PVC) and premature atrial contractions (PACs) The complaint alleges on information and belief that the algorithm in the Accused Watches performs a method for discriminating between AF and PVC/PACs. ¶120 col. 19:42-46
demarcating boundaries in a Poincare plot space... The algorithm allegedly demarcates boundaries in a Poincare plot space, with the boundaries obtained from a test set of test subjects. ¶121 col. 19:47-51
constructing a Poincare plot of time interval data from a subject under test... The algorithm allegedly constructs a Poincare plot using time interval data obtained by sensing variability in the user's heart rate signal. ¶123 col. 19:52-59
identifying data in patterns in the Poincare plot, the patterns including patterns corresponding to combinations of at least one of bigeminy, trigemini, and quadragemini indicating one of PAC or PVC; The algorithm allegedly identifies specific arrhythmia patterns such as bigeminy, trigemini, and quadragemini in the Poincare plot. ¶124 col. 19:59-64
obtaining updated data by subtracting the data in the patterns...from the time interval data from the subject under test; The algorithm allegedly obtains updated data by subtracting the data corresponding to the identified patterns from the original time interval data. ¶125 col. 19:64-20:1
obtaining a root mean squared of successive differences, a Shannon entropy and a turning point ratio for the updated data; The algorithm allegedly calculates these three statistical metrics on the "updated data" created in the previous step. ¶126 col. 20:2-5
comparing the root mean square..., the Shannon entropy..., and the turning point ratio to...predetermined threshold[s]; The algorithm allegedly compares the three calculated metrics against three respective predetermined thresholds. ¶127 col. 20:6-12
determining, if each of the...[metrics] is not less than a corresponding predetermined threshold, that the subject under test has atrial fibrillation... Based on the comparisons, the algorithm allegedly determines that the user has AF. ¶128 col. 20:12-18
  • Identified Points of Contention:
    • Technical Question: Claim 1 recites a highly specific, multi-step process: constructing a Poincare plot, identifying specific patterns (e.g., "bigeminy"), subtracting the data for those patterns to create "updated data," and only then analyzing that "updated data." This raises a significant technical question: does the accused algorithm actually perform this precise sequence of identifying, subtracting, and then analyzing modified data, or does it use a different method to discriminate between AF and other arrhythmias?
    • Scope Question: The claim requires "demarcating boundaries in a Poincare plot space, the boundaries being obtained from data from a test set of test subjects." This raises the question of whether the accused algorithm uses pre-defined boundaries derived from a specific test set, and what evidence supports this allegation.

V. Key Claim Terms for Construction

For the ’326 Patent:

  • The Term: "detecting a likelihood of AF"
  • Context and Importance: This term appears in the final step of Claim 1. Its construction is critical because the claim requires detecting AF by performing three specific calculations (TPR, RMSSD, SE). The dispute may turn on whether simply providing a general AF alert, without performing all three specific calculations, meets this limitation. Practitioners may focus on whether this requires the output to be based on the combination of all three metrics, or if using any one of them would suffice.
  • Intrinsic Evidence for Interpretation:
    • Evidence for a Broader Interpretation: The claim language "detecting a likelihood of AF by" could be argued to encompass any detection process that uses these calculations, without necessarily requiring all three to be dispositive.
    • Evidence for a Narrower Interpretation: The detailed description repeatedly discusses the combination of these statistics as providing the inventive advantage (’326 Patent, col. 4:51-67). The patent abstract also refers to providing an "overall accuracy that refers to detection of AF," suggesting a comprehensive analysis rather than a piecemeal one.

For the ’576 Patent:

  • The Term: "obtaining updated data by subtracting the data in the patterns"
  • Context and Importance: This is a central and unconventional step in Claim 1. The infringement allegation hinges on whether the accused algorithm literally subtracts and removes data points corresponding to PVC/PAC patterns before analyzing the remaining data for AF. Practitioners may focus on this term because it describes a specific data manipulation step that is technically distinct from merely classifying different arrhythmias.
  • Intrinsic Evidence for Interpretation:
    • Evidence for a Broader Interpretation: A defendant might argue this term could cover any algorithmic process that computationally filters or de-weights data points identified as PACs/PVCs, even without literal subtraction.
    • Evidence for a Narrower Interpretation: The plain language "subtracting the data" suggests a direct removal of data points. The patent specification describes this step as "subtracting the identified patterns from the original signal" to create an "updated signal," which is then analyzed separately (’576 Patent, Fig. 3). This supports a literal interpretation requiring a two-stage process of data removal followed by analysis of the remainder.

VI. Other Allegations

  • Indirect Infringement: The complaint alleges that Huawei induces infringement by marketing, advertising, and providing user manuals for the Accused Watches and the Huawei Health app (Compl. ¶¶111, 138). These materials allegedly instruct and encourage end-users and retailers to use the products in a way that performs the patented methods of physiological monitoring.
  • Willful Infringement: Willfulness is alleged based on Huawei's purported knowledge of the patents-in-suit and their infringement "since at least the filing of this Complaint" (Compl. ¶¶113, 140). This appears to be a claim for post-filing willfulness, asserting that any continued infringement after receiving notice via the lawsuit is deliberate and intentional.

VII. Analyst’s Conclusion: Key Questions for the Case

  • A central evidentiary issue will be one of algorithmic transparency: can Plaintiffs produce evidence, likely through source code review during discovery, to demonstrate that the accused Huawei watches' internal algorithms perform the specific, multi-step statistical analyses recited in the asserted claims (e.g., calculating Shannon Entropy, identifying and subtracting Poincare plot patterns), as opposed to more general-purpose methods for heart rate monitoring and arrhythmia detection?
  • A key question of technical operation will be whether the accused products, which use PPG sensors to measure blood volume changes, function in a manner that is equivalent to the patented methods, which are often described in the context of analyzing "RR intervals" from ECG signals. The case may require expert testimony to establish whether data derived from these different sensor types is processed in a technically analogous way to meet the claim limitations.