Mobile Health Innovative Solutions LLC v. Binahai Inc

I. Executive Summary and Procedural Information

• Parties & Counsel:
  • Plaintiff: Mobile Health Innovative Solutions, LLC (Wyoming)
  • Defendant: Binah.ai Inc. (Delaware)
  • Plaintiff’s Counsel: Lambert Shortell & Connaughton
• Case Identification: 1:24-cv-12635, D. Mass., 10/17/2024
• Venue Allegations: Venue is alleged to be proper based on Defendant maintaining a regular and established business presence in the District of Massachusetts.
• Core Dispute: Plaintiff alleges that Defendant’s AI-based Health Data Platform infringes a patent related to using mobile device sensors and application data to establish a user's current stress or load level.
• Technical Context: The technology at issue operates in the digital health and mobile wellness sector, where smartphone capabilities are leveraged for non-invasive monitoring of physiological and behavioral metrics.
• Key Procedural History: The complaint notes that the patent-in-suit was examined by a specific USPTO examiner and argues that the patent is presumptively valid over prior art considered during prosecution.

Case Timeline

Date	Event
2012-08-01	’984 Patent Priority Date
2022-10-11	’984 Patent Issue Date
2024-10-17	Complaint Filing Date

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 addresses the shortcomings of prior art methods for determining a user's stress level, which were seen as unreliable because they relied on limited data (e.g., a single vital sign) or required users to wear special, cumbersome sensor devices, restricting comfort and convenience (’984 Patent, col. 2:4-24). Questionnaire-based methods were also noted to require a high level of effort from the user (’984 Patent, col. 2:28-34).
• The Patented Solution: The invention proposes using a software application on a standard mobile device (e.g., a smartphone) that ascertains a "multiplicity of biometric data" for the user (’984 Patent, col. 2:56-58). This is achieved by combining data from the device's integrated sensors (like gyroscopes or microphones) with "user data" extracted from other "available applications" on the device, such as telephony or SMS applications (’984 Patent, col. 3:29-44). This combination of data from multiple categories allows for a more reliable determination of a user's "load level" without requiring additional hardware.
• Technical Importance: This approach capitalized on the expanding sensor suites and computational power of ubiquitous mobile devices to create a low-cost, non-intrusive method for comprehensive wellness monitoring (’984 Patent, col. 2:35-54).

Key Claims at a Glance

• The complaint asserts independent claim 1 and reserves the right to assert other claims (Compl. ¶26).
• The essential elements of independent claim 1 include:
  • A device for calculating a user's current load level, comprising a mobile end unit.
  • The mobile end unit must have: at least one integrated sensor, a plurality of available applications, and an evaluation unit (which can be on the device or a central server).
  • The mobile unit runs a "further application" that calculates biometric data from both the integrated sensor(s) and from "user data" of the other available applications.
  • The biometric data is divided into multiple categories, and category-specific load levels are ascertained.
  • The overall current load level is determined from the biometric data using a "network of artificial neural networks" that includes a "plurality of artificial neural networks that interact with each other."
  • The final load level is displayed to the user.

III. The Accused Instrumentality

Product Identification

Defendant's "Health Data Platform" ("Products") (Compl. ¶26).

Functionality and Market Context

The complaint describes the accused instrumentality as an "AI-based software solution that is installed on multiple devices such as smartphones... tablets, and laptops" (Compl. ¶26). Its function is "for calculating wellness score for the user" (Compl. ¶26). The complaint does not provide further technical details on the specific operation of the platform, but alleges that it performs the functions recited in the patent claims. No probative visual evidence provided in complaint.

IV. Analysis of Infringement Allegations

The complaint references a claim chart in its Exhibit B, which was not provided with the filed complaint. The following is a summary of the infringement theory based on the narrative allegations. (Compl. ¶¶26, 32, 35).

The Plaintiff alleges that the Defendant's Health Data Platform, an AI-based software solution for calculating a user's wellness score, infringes at least Claim 1 of the ’984 Patent (Compl. ¶26). The complaint asserts that the accused products satisfy all elements of Claim 1, and that a detailed comparison is provided in the unattached Exhibit B (Compl. ¶32).

The complaint also advances a theory of divided infringement, anticipating that some claim steps may be performed by the end-user rather than the Defendant directly (Compl. ¶33). Citing Travel Sentry, Inc. v. Tropp, Plaintiff argues that Defendant is nonetheless liable for direct infringement because it distributes product literature and instructions that direct customers on how to use the products in an infringing manner to obtain the benefit of a "current load level" calculation (Compl. ¶¶33-34).

V. Key Claim Terms for Construction

The Term: "further application"

• Context and Importance: This term defines the core inventive software. The infringement analysis may turn on whether the accused "Health Data Platform" is structurally and functionally equivalent to the "further application," particularly regarding its claimed ability to collect data from both built-in sensors and other "available applications."
• Intrinsic Evidence for a Broader Interpretation: The patent describes the invention as comprising a "further application that can be installed on a mobile terminal" which "interacts with other components that are likewise arranged in the mobile terminal," such as sensors and available applications (’984 Patent, col. 2:56-62). This could support a reading that covers a wide range of installable wellness apps.
• Intrinsic Evidence for a Narrower Interpretation: The specification describes specific implementations, such as using an "observer design pattern" to monitor status changes in an SMS application (’984 Patent, col. 8:38-56). Parties may dispute whether the accused product must practice such specific disclosed software design patterns to meet this limitation.

The Term: "user data of said plurality of available applications"

• Context and Importance: This limitation is central to distinguishing the invention from prior art that relied only on dedicated sensors. Practitioners may focus on this term because infringement requires proof that the accused product extracts and uses data derived from other, general-purpose applications (e.g., SMS, telephony) on a user's device.
• Intrinsic Evidence for a Broader Interpretation: The patent suggests this can include broad data types, such as recording "all keypad inputs by the user... regardless of their use in a specific application" (’984 Patent, col. 7:61-63). This language may support a broad definition of "user data."
• Intrinsic Evidence for a Narrower Interpretation: The specification also provides very specific examples, such as analyzing "characters input by the user" in an SMS application or analyzing "voice data from telephone calls" (’984 Patent, col. 8:50-56; col. 15:43-47). This could support a narrower construction requiring the extraction of granular, content-level data from other applications, not just high-level metadata.

The Term: "network of artificial neural networks that includes a plurality of artificial neural networks that interact with each other"

• Context and Importance: This limitation defines the specific analytical engine required by the claim. The dispute will likely center on whether Defendant's "AI-based software solution" (Compl. ¶26) uses an architecture that meets this definition.
• Intrinsic Evidence for a Broader Interpretation: The claim language itself is somewhat general, and could be argued to cover various modern AI systems where multiple models or sub-networks collaborate to produce a final output (’984 Patent, col. 23:18-24).
• Intrinsic Evidence for a Narrower Interpretation: The specification describes detailed embodiments, including "a Deep Belief Network" and a hierarchical structure where the "input layer" of a higher-level network is "determined using the hidden layers of a plurality of neural networks on the preceding level" (’984 Patent, col. 6:38-41, col. 21:57-62). These specific architectural descriptions could be used to argue for a more constrained definition of the required "network" and "interaction."

VI. Other Allegations

Indirect Infringement

The complaint alleges both induced and contributory infringement of at least Claim 1 (Compl. ¶¶30-31). Inducement is based on allegations that Defendant provides "product literature and website materials" that instruct and encourage customers to use the products in an infringing manner (Compl. ¶29). Contributory infringement is based on allegations that the accused products have "special features that are specially designed" for an infringing use and are not "staple articles of commerce suitable for substantial non-infringing use" (Compl. ¶31).

Willful Infringement

The complaint alleges that Defendant has had "actual knowledge of infringement" at least since the service of the complaint and that it "continues to make, use, test, sell, offer for sale, market, and/or import" the accused products despite this knowledge (Compl. ¶¶28-29). These allegations may form the basis for a claim of post-filing willful infringement and a request for enhanced damages.

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

• A core issue will be one of data sourcing: can Plaintiff produce evidence that the accused "Health Data Platform" actually extracts and analyzes "user data of said plurality of available applications" (such as SMS or call logs), as required by Claim 1, or does the platform operate in a silo, relying only on its own inputs and direct sensor access?
• A key evidentiary question will be one of architectural correspondence: does the defendant’s "AI-based software solution" implement the claimed "network of artificial neural networks that interact with each other," or does it utilize a different, non-infringing AI architecture, such as a single monolithic model or a simple, non-interactive ensemble?
• An important legal question will concern divided infringement: assuming end-user actions are required to practice the full claim, can Plaintiff demonstrate that Defendant directs or controls its users' performance of the claimed steps to such a degree that their actions can be attributed to Defendant for the purpose of finding direct infringement?