Mobile Health Innovative Solutions LLC v. Zepp Health Corp

I. Executive Summary and Procedural Information

• Parties & Counsel:
  • Plaintiff: Mobile Health Innovative Solutions, LLC (Wyoming)
  • Defendant: Zepp Health Corporation (China) and Zepp North America, Inc. (Delaware)
  • Plaintiff’s Counsel: Garteiser Honea—IP Trial Boutique
• Case Identification: 2:24-cv-01030, C.D. Cal., 02/06/2024
• Venue Allegations: Plaintiff alleges venue is proper for Zepp Health Corporation as a foreign entity and for Zepp North America, Inc. based on its alleged maintenance of a regular and established business presence, including physical locations and employees, within the Central District of California.
• Core Dispute: Plaintiff alleges that Defendant’s Amazfit smartwatches and the associated Zepp Aura service infringe a patent related to determining a user's physiological "load level" by analyzing biometric data gathered from both device sensors and user interactions with various applications.
• Technical Context: The technology operates within the wearable health-tech sector, where devices like smartwatches leverage integrated sensors and software to monitor and analyze user biometrics for health and wellness insights.
• Key Procedural History: The complaint notes that the patent-in-suit was examined by USPTO Examiner Rex R. Holmes, who considered a field of prior art including U.S. patents, published applications, and other publications before allowing the claims to issue.

Case Timeline

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

U.S. Patent No. 11,468,984 - "Device, Method and Application for Establishing a Current Load Level," issued October 11, 2022

The Invention Explained

• Problem Addressed: The patent describes prior art methods for determining a user's stress level as being disadvantaged by their reliance on "very few biometric data" points (e.g., only objective sensor data or only subjective questionnaire data), which can be unreliable. Furthermore, methods relying on specialized, wearable sensor devices were identified as costly and potentially uncomfortable for the user. (’984 Patent, col. 2:4-24).
• The Patented Solution: The invention proposes using a general-purpose "mobile terminal" (e.g., a smartphone) with a "further application" installed. This application is configured to establish a user's "current load level" by ascertaining a "multiplicity of biometric data" derived not only from the device's integrated sensors (like gyroscopes or accelerometers) but also from the user's interaction with other "available applications" (such as telephony or SMS applications). An evaluation unit then analyzes this combined data to determine the load level. (’984 Patent, Abstract; col. 2:56-65).
• Technical Importance: The described approach leverages the existing and expanding sensor and software capabilities of ubiquitous mobile devices, aiming to provide a more reliable and comprehensive assessment of user stress without requiring additional, specialized hardware. (’984 Patent, col. 2:45-53).

Key Claims at a Glance

• The complaint asserts independent claims 1 (a device claim) and 12 (a method claim) ('Compl. ¶28).
• Independent Claim 1 requires:
  • A "mobile end unit" comprising at least one integrated sensor, a plurality of available applications, and an evaluation unit.
  • A "further application" for calculating biometric data from both the sensor's signal data and from "user data" of the available applications.
  • The division of biometric data into a "plurality of categories" from which "category-specific load levels" are ascertained.
  • An evaluation unit that determines the "current load level" by applying a method carried out in a "network of artificial neural networks that includes a plurality of artificial neural networks that interact with each other."
  • A "plurality of processors" arranged to calculate the neural networks in parallel.
  • A display of the determined load level to the user as a "consolidated load level."
• Independent Claim 12 requires:
  • Starting a "further application" on a mobile end unit.
  • Calculating biometric data from both sensor signal data and user data from available applications.
  • Dividing the biometric data into categories and evaluating it with an evaluation unit using a "network of artificial neural networks."
  • Calculating the network in parallel with a "plurality of processors."
• The complaint alleges infringement of "one or more claims, including at least Claims 1, 5, 11 and 12," thereby reserving the right to assert additional dependent claims (Compl. ¶28).

III. The Accused Instrumentality

Product Identification

• The "Accused Instrumentalities" are identified as "Amazfit smartwatches such as the Amazfit GTR 4 (Watch)" and the "Zepp Aura" service (Compl. ¶23).

Functionality and Market Context

• The complaint alleges the accused products provide an "AI-powered solution" that measures the "readiness and relaxation level" of users, which the Plaintiff equates to the "current load level" of the patent (Compl. ¶23).
• The stated function of the products is to help users "understand their sleeping patterns" (Compl. ¶2). The complaint does not provide specific technical details on the products' operation beyond these high-level functional descriptions.
• Figure 2 of the complaint provides a Google Maps street view image of the alleged business location for Zepp North America, Inc. in Milpitas, California, which is offered as evidence to support venue allegations (Compl. p. 4, Fig. 2).

IV. Analysis of Infringement Allegations

The complaint references an infringement claim chart, attached as Exhibit B, which was not included with the filed complaint. Therefore, the infringement allegations are summarized in prose based on the complaint's narrative.

The complaint alleges that the Accused Instrumentalities directly infringe at least claims 1 and 12 of the ’984 Patent (Compl. ¶¶28-29). The infringement theory appears to map the Amazfit smartwatch to the "mobile end unit" and the Zepp Aura service to the "further application" and "evaluation unit" recited in the claims (Compl. ¶23). Plaintiff alleges that the accused system measures a "readiness and relaxation level" by collecting and analyzing biometric data, which it contends is the "current load level" taught by the patent (Compl. ¶23). The "AI-powered" nature of the solution is alleged to meet the "network of artificial neural networks" limitation (Compl. ¶23). The complaint incorporates the unfiled Exhibit B by reference, stating that it sets forth a comparison of the claims to the Accused Instrumentalities that satisfies all claim elements (Compl. ¶¶33-34).

Identified Points of Contention

• Scope Questions: A question for the court may be whether the accused system, described as helping users "understand their sleeping patterns" (Compl. ¶2), meets the claim requirement of calculating biometric data from both "signal data produced by said at least one sensor" and "user data of said plurality of available applications used by the user" (’984 Patent, cl. 1). The patent specification provides examples of "user data" from applications such as telephony, SMS, and web browsing, raising the question of whether the accused system analyzes data from such a plurality of applications. (cf. ’984 Patent, col. 2:62-65).
• Technical Questions: A factual dispute may arise over whether the "AI-powered solution" alleged to be part of the accused system (Compl. ¶23) constitutes a "network of artificial neural networks that includes a plurality of artificial neural networks that interact with each other" as structurally required by claim 1. The complaint does not provide evidence regarding the specific architecture of the AI used in the Accused Instrumentalities.

V. Key Claim Terms for Construction

"user data of said plurality of available applications used by the user" (from claim 1)

• Context and Importance: This term is central to the scope of the invention, as it distinguishes the patented method from systems that rely solely on dedicated sensor data. The infringement analysis will depend on whether the data analyzed by the Accused Instrumentalities is found to originate from a "plurality of available applications" as construed. Practitioners may focus on this term because the complaint's description of the accused product centers on sleep analysis (Compl. ¶2), which may or may not involve data from a plurality of distinct user applications.
• Intrinsic Evidence for Interpretation:
  • Evidence for a Broader Interpretation: The specification lists broad examples of available applications, including "telephony, SMS, MMS, chat applications and/or browser applications," suggesting the term could encompass a wide range of standard mobile device software (’984 Patent, col. 2:62-65).
  • Evidence for a Narrower Interpretation: The detailed embodiments describe extracting specific behavioral metrics from these applications, such as "the number of SMS messages sent and received" and analysis of keypad input patterns (’984 Patent, col. 4:58-63; col. 19:51-60). This could support a narrower construction requiring analysis of active user communication or interaction, rather than just passive data collection.

"network of artificial neural networks that includes a plurality of artificial neural networks that interact with each other" (from claim 1)

• Context and Importance: This term defines the specific computational architecture of the "evaluation unit." The infringement case hinges on whether the accused "AI-powered solution" (Compl. ¶23) implements this specific structure. The term's construction will determine the level of architectural complexity required to infringe.
• Intrinsic Evidence for Interpretation:
  • Evidence for a Broader Interpretation: The claim language itself does not limit the type or configuration of the interacting neural networks, which may support a construction covering any system with multiple, interconnected neural network components.
  • Evidence for a Narrower Interpretation: The specification describes specific, complex architectures, including "a deep belief network or a convolutional deep belief network" and hierarchical systems where hidden layers of one network level feed the input layers of the next (’984 Patent, col. 21:35-51). This language may be used to argue that the claim requires a specific, multi-level network structure rather than a more general AI model.

VI. Other Allegations

• Indirect Infringement: The complaint alleges inducement of infringement, stating that Defendants distribute "product literature and website materials" that instruct end users to use the accused products in a manner that infringes the ’984 Patent (Compl. ¶31).
• Willful Infringement: The complaint alleges willful infringement based on Defendants' knowledge of the ’984 Patent obtained "at least as of the service of the present complaint" (Compl. ¶26). It further alleges that Defendants' continued infringement, despite the actual knowledge provided by the complaint and its referenced claim chart, is intentional and willful (Compl. ¶¶31-32).

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

1. A core issue will be one of data sourcing: Can the term "user data of said plurality of available applications," which the patent specification links to activities like messaging and phone calls, be construed to read on the data collected by the accused Zepp system, which the complaint primarily describes in the context of analyzing "sleeping patterns"?
2. A key evidentiary question will be one of architectural equivalence: Does the accused "AI-powered solution" embody the specific structure of a "network of artificial neural networks that includes a plurality of artificial neural networks that interact with each other" and that is calculated "in parallel," as required by the claims, or is there a fundamental mismatch in technical architecture between the patent's detailed requirements and the defendant's system?