US 6537227

Here is a concise summary of US patent 6537227:

US Patent 6537227: Method and equipment for human-related measuring

• Title: Method and equipment for human-related measuring
• Assignee: Polar Electro Oy
• Inventors: Hannu Kinnunen, Seppo Nissilä
• Filing Date: 2001-03-02
• Issue Date: 2003-03-25
• Abstract: A heart rate measuring arrangement including measuring means for measuring a person's heart rate during exercise and a calculating unit for calculating an assessment of the person's energy consumption during exercise. This calculation uses at least two parameters: a heart rate parameter from measured heart rate information and an energy consumption reference value. The reference value is derived from one or more performance parameters that describe the person's physical performance. The arrangement also includes presenting means for displaying this energy consumption assessment.

CAFC 2026 Dockets:
As of April 26, 2026, there are no new CAFC dockets for US Patent 6537227 in the provided search results. However, related litigation is ongoing concerning this patent. Polar Electro Oy, the patent owner, has filed a petition (No. 25-1268) with the U.S. Supreme Court in May 2026, challenging a Federal Circuit affirmation (Rule 36) of a district court's summary judgment of patent ineligibility under 35 U.S.C. § 101. This Supreme Court petition follows a Federal Circuit decision that occurred prior to 2026, affirming the district court's finding that the claims were patent-ineligible.

Independent Claims Overview:

Please note: The original independent claims (Claim 1 and Claim 16) as initially granted were cancelled during reexamination proceedings. While subsequent reexamination certificates indicate that various original dependent claims were amended to be patentable (e.g., Claims 2-6, 11, 15, 17-22, 27, 31, 33, 37, 38) and new claims were added (Claims 32-42, 43-46, 47-52), the specific text of these currently valid independent claims is not available in the provided patent document. Therefore, a plain-language overview of the current independent claims cannot be provided with authoritative detail.

Known litigation involving US patent 6537227 includes the following:

1. Polar Electro Oy v. Suunto Oy, Amer Sports Winter & Outdoor, and Firstbeat Technologies Oy

• Plaintiff(s): Polar Electro Oy
• Defendant(s): Suunto Oy, Amer Sports Winter & Outdoor (ASWO), Firstbeat Technologies Oy
• Jurisdiction: United States District Court for the District of Delaware
• Case Number: 1:11-cv-01100
• Filing Date: Approximately 2011 (based on case number and reported appeal timeline)
• Outcome/Current Status: The District Court dismissed the complaint against Suunto Oy for lack of personal jurisdiction. Polar Electro Oy appealed this dismissal. ASWO and Firstbeat Technologies Oy remained in the suit at the district court level. The Federal Circuit case numbers 15-1927 and 15-1930 are associated with this litigation family, likely representing appeals related to this case. The specific outcome of the Federal Circuit appeal regarding Suunto Oy is not detailed in the provided information.

2. Polar Electro Oy v. Firstbeat Technologies Oy

• Plaintiff(s): Polar Electro Oy
• Defendant(s): Firstbeat Technologies Oy (acquired by Garmin in 2020)
• Jurisdiction: United States District Court for the District of Utah; Court of Appeals for the Federal Circuit; Supreme Court of the United States
• Case Number: 1:17-cv-00139 (Utah District Court); 24-1801 (Court of Appeals for the Federal Circuit); 25-1268 (U.S. Supreme Court petition)
• Filing Date: Utah District Court case filed in 2017. The Supreme Court petition (No. 25-1268) is to be filed in May 2026.
• Outcome/Current Status: In the Utah District Court, Firstbeat Technologies Oy was granted summary judgment of patent ineligibility under 35 U.S.C. § 101. The Federal Circuit affirmed this decision without opinion (Rule 36). Polar Electro Oy is challenging this affirmation and plans to file a petition for certiorari with the U.S. Supreme Court (No. 25-1268) in May 2026, raising questions concerning judicial construction of invalidity arguments, the patent eligibility of processes utilizing real-world physiological inputs for improved technological outcomes, and the permissibility of judicially created exceptions to patent eligibility.

Proceedings overview

There are no AIA trial proceedings (Inter Partes Review, Post-Grant Review, or Covered Business Method) on file for US Patent 6537227 as of the most recent USPTO Open Data Portal ingest. This means the patent has not been subjected to the types of post-grant challenges introduced by the America Invents Act. However, the patent has undergone three reexamination proceedings, significantly altering its claim scope and validity. These reexaminations resulted in the cancellation of original independent claims 1 and 16, and the amendment and addition of numerous other claims, providing a defendant with a clear understanding of the patent's narrowed scope.

Reexamination Proceedings

While no AIA trial proceedings are on record, US Patent 6537227 underwent three reexamination proceedings, which are also conducted by the Patent Trial and Appeal Board (PTAB) and significantly impacted the patent's claims. These are distinct from IPR, PGR, or CBM trials.

First Reexamination (Certificate B1)

• Request Filed: 2012-11-27
• Certificate Issued: 2013-06-11
• Outcome:
  • Claims Cancelled: Original Claims 1 and 16. These were the only independent claims initially granted.
  • Claims Amended/Determined Patentable: Claims 2-6, 11, 15, 17-22, 27, and 31 were determined to be patentable as amended.
  • Claims Dependent on Amended Claims: Claims 7-10, 12-14, 23-26, and 28-30 were determined to be patentable.
  • New Claims Added: Claims 32-42 were added and determined to be patentable.
• Defensive value: This reexamination critically eliminated the original independent claims. Any assertion of the patent must now rely on the amended or new claims, significantly narrowing the scope of potential infringement.

Second Reexamination (Certificate B2)

• Request Filed: 2014-04-08
• Certificate Issued: 2014-10-07
• Outcome:
  • Claims Previously Cancelled: Claims 1 and 16 remained cancelled.
  • Claims Amended/Determined Patentable: Claims 5, 6, 17, 18, 21, 22, 33, 37, and 38 were determined to be patentable as amended.
  • Claims Dependent on Amended Claims: Claims 2-4, 7-15, 19, 20, 23-32, 34-36, and 39-42 were determined to be patentable.
  • New Claims Added: Claims 43-46 were added and determined to be patentable.
• Defensive value: This further refined the scope of the remaining claims, confirming previous cancellations and continuing the process of amendment and addition. A defendant needs to evaluate the specific amendments to these claims.

Third Reexamination (Certificate C3)

• Request Filed: 2016-02-16
• Certificate Issued: 2017-03-28
• Outcome:
  • Claims Previously Cancelled: Claims 1 and 16 remained cancelled.
  • Claims Confirmed Patentable: The patentability of Claims 2-15 and 17-46 was confirmed.
  • New Claims Added: Claims 47-52 were added and determined to be patentable.
• Defensive value: This final reexamination confirmed the patentability of a broad range of claims (2-15, 17-46, and 47-52) after multiple rounds of review, suggesting they are robust against the prior art considered during these proceedings.

Strategic summary

Claims 1 and 16, the original independent claims of US Patent 6537227, are CANCELED. The patent now relies on claims 2-15, 17-46, and the newly added claims 47-52. These claims have been through multiple reexamination proceedings at the USPTO, indicating that they have survived challenges based on prior art presented during those examinations. The patent has been significantly narrowed and particularized through these processes.

Regarding the estoppel landscape, since these were reexaminations (and not IPRs/PGRs/CBMs as specifically defined by AIA trial proceedings), the specific statutory estoppel provisions of 35 U.S.C. § 315(e)(2) for IPRs do not directly apply to potential future petitioners. However, any prior art successfully argued during these reexaminations to distinguish the confirmed claims would be a strong indication of their patentability. Moreover, a party that requested one of these reexaminations might face common law estoppel if attempting to re-litigate the same prior art grounds in district court against claims confirmed in reexamination. Given the lack of specific petitioner names in the provided legal events, these likely originated as ex parte reexaminations (meaning the PTO itself initiated or a third party requested it without becoming a full party to the proceeding), or inter partes reexaminations filed before the AIA effectively ended new filings for that type. The multiple reexaminations suggest that the patent owner, Polar Electro Oy, actively defended and modified the patent's claims to ensure their validity against various prior art challenges.

Recommended next steps

For a defendant facing assertion of US Patent 6537227:

• Review the Reexamination Certificates: Obtain and thoroughly analyze the full text of reexamination certificates B1, B2, and C3 (accessible via USPTO PatentCenter or Public Pair by the publication number, e.g., US6537227C3). These certificates provide the exact amended claim language and the examiner's reasoning for confirming patentability. This is critical for understanding the current scope of the claims.
• Focus on Surviving Claims: Any infringement assertion should carefully identify which of the currently valid claims (2-15, 17-46, and 47-52) are being alleged. If the assertion relies on original claims 1 or 16, the plaintiff's position is baseless given their cancellation.
• Analyze Reexamination History for Prior Art: Examine the prior art cited and discussed during the reexaminations. While new AIA trial proceedings are not barred by these reexaminations, understanding the prior art that the patent owner successfully distinguished can inform potential new invalidity arguments or reframe existing ones. The confirmation of claims 2-15, 17-46, and 47-52 indicates that they were deemed patentable over the art considered.
• Absence of AIA Trials: The lack of IPR, PGR, or CBM proceedings means that the patent's claims have not been challenged under the specific rules and heightened estoppel provisions of AIA trials. This could represent both an opportunity (less specific statutory estoppel) and a challenge (the claims have not been subjected to the unique trial procedures of the PTAB's AIA proceedings).
• District Court Litigation: Given the ongoing litigation (Polar Electro Oy v. Firstbeat Technologies Oy, Case No. 1:17-cv-00139) that resulted in a summary judgment of patent ineligibility under 35 U.S.C. § 101, a defendant should carefully consider the Section 101 arguments that were successful at the district court and Federal Circuit levels. This could be a significant defensive avenue. The Supreme Court petition (No. 25-1268) regarding this Section 101 issue is a critical development to monitor.

Inventors

• Hannu Kinnunen (Polar Electro Oy)
• Seppo Nissilä (Polar Electro Oy)

No unusual patterns observed regarding inventors departing the original assignee.

Original assignee

Polar Electro Oy is the original assignee. Polar Electro Oy is a Finnish company known for manufacturing heart rate monitors and other wearables for sports and fitness. They ship products embodying the claims. The company is currently operating.

Assignment timeline

• 2001-02-19 (executed) / recorded 2001-03-02 — Reel 011586/0854
  • Conveyance: ASSIGNMENT
  • Assignor: KINNUNEN, HANNU; NISSILA, SEPPO
  • Assignee: POLAR ELECTRO OY
  • Correspondent: NOT LISTED
  • Context: Original assignment from inventors to operating company prior to filing.

The USPTO Assignment Center search for US6537227 shows only one record: the initial assignment from the inventors to Polar Electro Oy (Reel 011586/0854). This indicates that, according to public assignment records, Polar Electro Oy remains the owner of the patent.

Timeline diagram

timeline
    title Ownership of US 6537227
    2001 : Assigned to Polar Electro Oy
    2001 : Patent filed
    2003 : Patent issued

NPE / troll-pattern signals

1. Shell-entity transfer — Not present. The only recorded assignment is from the inventors to Polar Electro Oy, an operating company.
2. Known asserter in the chain — Not present. Polar Electro Oy is an operating company, not a known NPE.
3. Repeat correspondent across the chain — Not present. Only one assignment is recorded, and the correspondent is not listed.
4. Cascading transfers — Not present. Only one assignment is recorded.
5. Pre-litigation transfer — Not present. The initial assignment occurred before the patent was even filed. The recorded litigation dates are significantly later than the assignment date.
6. Bankruptcy fire-sale — Not present. There is no indication that Polar Electro Oy has filed for bankruptcy.
7. Privateering — Unclear. While Polar Electro Oy is involved in litigation, there is no public record indicating a transfer to an NPE for assertion on their behalf. They are the direct plaintiff in the noted lawsuits.
8. Defensive aggregator (anti-NPE) — Not present. The patent is not currently assigned to a defensive aggregator.

Verdict

Operating-company assertion. The only recorded assignment shows the patent transferred from the inventors to Polar Electro Oy (Reel 011586/0854), an established operating company that produces products related to heart rate monitoring. Polar Electro Oy is also the direct plaintiff in the noted litigation, indicating they are asserting the patent on their own behalf as an operating company.

Verification: https://assignmentcenter.uspto.gov/patent/index.html?cn=US6537227B2

To identify the most relevant prior art for US patent 6537227, I will examine the "Citations" section of the patent document itself. The patent document lists "Cited By" (patents that cite 6537227) and "Citations" (prior art cited against 6537227). For this task, "Citations" are the relevant prior art.

I will use the provided patent text to extract the citations, as direct access to the USPTO database for live search of citation details for a specific patent is not within my capabilities in this interactive format beyond what is already included in the provided patent text.

Based on the provided patent text, the following prior art documents are cited:

Most Relevant Prior Art for US Patent 6537227

Here are the prior art references cited in US Patent 6537227, along with available details:

1. US4566461A

   • Full Citation: US4566461A
   • Publication Date: 1986-01-28
   • Filing Date: 1983-02-15
   • Assignee: Michael Lubell
   • Description: "Health fitness monitor." This patent describes a monitor for health and fitness, which could be relevant to the general concept of monitoring physiological parameters during exercise.
   • Potential Anticipated Claims: Given its broad description as a "health fitness monitor," it could potentially anticipate aspects of claims related to measuring heart rate information (e.g., portions of claims 1, 15, 16) and displaying information, but likely lacks the specific calculation methodology involving energy consumption reference values derived from performance parameters. More specific analysis of the claims of US6537227 and US4566461A would be needed for a definitive statement.

2. US5297558A

   • Full Citation: US5297558A
   • Publication Date: 1994-03-29
   • Filing Date: 1993-03-12
   • Assignee: Medical Graphics Corporation
   • Description: "Algorithm for prescribing an exercise regimen to enhance fat burning and cardiovascular fitness." This patent focuses on algorithms for exercise regimens, which might involve calculations related to physiological responses.
   • Potential Anticipated Claims: This patent could potentially anticipate methods involving the assessment of physiological states during exercise and using algorithms for fitness, possibly touching upon claims related to calculating energy consumption (e.g., claims 1, 16) or using physiological parameters. The distinct feature of US6537227 being the use of energy consumption reference values from performance parameters would need to be carefully compared.

3. JPH0852119A

   • Full Citation: JPH0852119A
   • Publication Date: 1996-02-27
   • Filing Date: 1994-08-10
   • Assignee: Tanita:Kk
   • Description: "Calorie consumption." The title explicitly indicates a focus on calorie consumption measurement.
   • Potential Anticipated Claims: This appears highly relevant and could potentially anticipate claims 1 and 16 directly, especially those concerning assessing energy consumption during exercise. A detailed comparison would be needed to see if it utilizes "at least two calculating parameters, one of which is a heart rate parameter... and an energy consumption reference value obtained from one or more performance parameters."

4. US5640956A

   • Full Citation: US5640956A
   • Publication Date: 1997-06-24
   • Filing Date: 1995-06-07
   • Assignee: Neovision Corporation
   • Description: "Methods and apparatus for correlating ultrasonic image data and radiographic image data." This patent describes methods for correlating medical imaging data.
   • Potential Anticipated Claims: This patent appears to be less directly relevant to heart rate and energy consumption during exercise, focusing instead on medical imaging. It is unlikely to anticipate any claims in US6537227.

5. EP0845241A1

   • Full Citation: EP0845241A1
   • Publication Date: 1998-06-03
   • Filing Date: 1996-06-12
   • Assignee: Seiko Epson Corporation
   • Description: "Consumed calorie measuring apparatus and body temperature measuring apparatus." The title directly indicates a calorie consumption measuring apparatus.
   • Potential Anticipated Claims: Similar to JPH0852119A, this patent is highly relevant and could potentially anticipate claims related to assessing energy consumption (e.g., claims 1, 16). A careful comparison to ensure the specific calculation parameters of US6537227 are not present in this prior art would be necessary.

6. US5853351A

   • Full Citation: US5853351A
   • Publication Date: 1998-12-29
   • Filing Date: 1992-11-16
   • Assignee: Matsushita Electric Works, Ltd.
   • Description: "Method of determining an optimum workload corresponding to user's target heart rate and exercise device therefor." This patent discusses determining optimal workload based on heart rate.
   • Potential Anticipated Claims: This could be relevant to claims involving heart rate parameters and individualized exercise, potentially anticipating aspects of claims that use heart rate in calculations (e.g., claims 1, 11, 16, 27). The specific "energy consumption reference value" based on "performance parameters" as described in US6537227 would be a key differentiating factor.

7. US5976083A

   • Full Citation: US5976083A
   • Publication Date: 1999-11-02
   • Filing Date: 1997-07-30
   • Assignee: Living Systems, Inc.
   • Description: "Portable aerobic fitness monitor for walking and running." This patent describes a portable monitor for aerobic fitness.
   • Potential Anticipated Claims: This patent broadly covers fitness monitoring and could potentially anticipate aspects of US6537227 relating to measuring heart rate during exercise (claims 1, 15, 16) and presenting data. However, the unique method of assessing energy consumption through specific calculating parameters might differentiate US6537227.

8. US6361502B1

   • Full Citation: US6361502B1
   • Publication Date: 2002-03-26
   • Filing Date: 1997-05-21
   • Assignee: Polar Electro Oy
   • Description: "Non-invasive measuring device with different operating modes." This patent, also assigned to Polar Electro Oy, describes a non-invasive measuring device with various operating modes.
   • Potential Anticipated Claims: As it is from the same assignee and deals with measuring devices, it is plausible that it covers aspects of heart rate measurement (claims 1, 15, 16) and possibly even some level of data processing related to exercise. However, without a detailed review of its claims, it's hard to ascertain if it anticipates the specific energy consumption assessment method of US6537227.

It is important to note that the original independent claims (Claim 1 and Claim 16) were cancelled during reexamination. Therefore, the analysis of potential anticipation should ultimately focus on the currently valid claims (2-15, 17-46, and 47-52). A comprehensive anticipation analysis would require comparing the specific language of these surviving claims against the detailed disclosures of the prior art documents.

An obviousness analysis under 35 U.S.C. § 103 requires identifying combinations of prior art that would render the claims of US patent 6537227 obvious to a person having ordinary skill in the art (PHOSITA) at the time of the invention (priority date March 7, 2000). A PHOSITA in this field would possess knowledge in exercise physiology, biomedical engineering, or sports science, and be familiar with heart rate monitoring, energy expenditure calculation, and physiological modeling.

Critical Limitation: The original independent claims (Claim 1 and Claim 16) of US6537227 were cancelled during reexamination. While the patent now relies on amended dependent claims (2-15, 17-46) and newly added claims (32-42, 43-46, 47-52), the specific text of these currently valid independent claims is not available in the provided patent document. Therefore, this obviousness analysis must be conducted at a high level, focusing on the core inventive concepts described in the patent's abstract and detailed description, and acknowledging that specific claim language might introduce nuances not captured here.

Core Inventive Concept of US6537227:
The invention aims to provide an improved method and equipment for assessing a person's energy consumption during exercise. The key improvement over prior art is explicitly stated as taking into account that "a fit person performs a larger amount of work at a given heart rate level than an unfit person, whereby the amount of energy consumed by the fit person is larger than that of the unfit person."

The method achieves this by:

1. Measuring a person's heart rate information during exercise.
2. Assessing energy consumption using at least two calculating parameters:
   • A heart rate parameter.
   • An energy consumption reference value obtained from one or more performance parameters that describe the person's physical performance (with at least one being oxygen uptake, or parameters like speed/capacity).
3. Presenting the assessment.
4. The process typically involves a "personalizing phase" to establish a relationship (e.g., piecewise linear) between heart rate and energy consumption based on these performance parameters. This relationship often defines points like maximum, intermediate, and lower heart rates and corresponding energy consumption values.

Prior Art Combinations and Obviousness Analysis:

Combination 1: JPH0852119A (or EP0845241A1) in view of US5853351A and general physiological knowledge.

• JPH0852119A ("Calorie consumption") and EP0845241A1 ("Consumed calorie measuring apparatus") directly address the core function of measuring or assessing energy consumption (calories). A PHOSITA would understand that such devices would likely use heart rate as a primary input, as it is a widely recognized indicator of exercise intensity and thus energy expenditure.
• US5853351A ("Method of determining an optimum workload corresponding to user's target heart rate and exercise device therefor") teaches a method for determining an optimum workload based on a user's target heart rate. This reference inherently involves personalization, as an "optimum workload" would vary from person to person based on their individual fitness level and their physiological response (heart rate).
• Motivation for Combination: A PHOSITA would be motivated to combine the teachings of a calorie consumption measuring apparatus (JPH0852119A or EP0845241A1) with the personalization aspect of US5853351A. The stated problem in US6537227 – that prior art systems fail to account for different energy expenditures at the same heart rate for fit vs. unfit individuals – would drive a PHOSITA to seek more accurate and personalized energy consumption assessments. It would be obvious to improve the accuracy of a calorie consumption measurement device by incorporating a measure of individual physical performance or fitness. The use of "performance parameters" such as oxygen uptake (VO2max), running/swimming speed, or exercise bike resistance, are standard metrics in exercise physiology for quantifying physical performance. Therefore, a PHOSITA would find it obvious to use such performance parameters to derive an "energy consumption reference value" to personalize and refine the energy consumption calculations, rather than relying solely on generic heart rate-to-energy expenditure relationships. This would directly address the acknowledged deficiency of prior art.

Combination 2: Combination 1 further incorporating general knowledge of neural networks for physiological modeling.

• US6537227 describes the use of a neural network model to form the maximum value of a performance parameter (e.g., oxygen uptake) or to assess the maximum heart rate. The patent itself acknowledges that "The neural network is a way to model complex applications, such as... applications in physiological analysis, the presentation of which is very difficult as a mathematical model."
• Motivation for Combination: Given that neural networks were a known tool for modeling complex physiological data and relationships prior to the invention's priority date, a PHOSITA seeking to further refine the assessment of performance parameters or the heart rate-energy consumption relationship would be motivated to employ a neural network. If direct measurement of a performance parameter like VO2max is difficult, or if a more robust predictive model is desired, using a neural network to estimate these parameters based on more readily available physiological inputs (age, weight, height, gender) or exercise stress parameters would be an obvious application of known technology to a known problem in physiological modeling. The purpose would be to enhance the accuracy of the personalized energy consumption assessment.

Obviousness of Specific Calculation Details:
The patent describes determining specific points on the heart rate-energy consumption curve (e.g., lower heart rate at 50-60% of HRmax, lower energy consumption at 40% of EEmax, intermediate energy consumption at 75% of EEmax). While these percentages provide specific values, the patent states that EEmax is formed "in accordance with the known principles of human physiology", and the relationships are "substantially linear" or "piecewise linear." It would be obvious for a PHOSITA, through routine experimentation and drawing upon established principles of exercise energetics, to define such characteristic points and relationships to model an individual's energy consumption, especially when aiming to provide a more precise piecewise linear or curvilinear fit based on individual performance.

Conclusion:
Based on the general description of the invention, the core concept of personalizing energy consumption assessment using a heart rate parameter in conjunction with an energy consumption reference value derived from performance parameters (like oxygen uptake) appears to be an obvious combination of known elements in the prior art. The motivation stems from the known deficiency of prior art systems in accounting for individual fitness levels when calculating energy expenditure, a problem explicitly highlighted by the patent itself. The use of neural networks would represent a known tool applied to a known problem of physiological modeling.

However, it is crucial to reiterate that this analysis is limited by the absence of the exact text of the currently valid independent claims (which were extensively reexamined and amended). These claims may contain specific limitations that would overcome these obviousness arguments. A definitive obviousness determination would require a direct comparison of the full text of the surviving claims with the disclosures of the identified prior art.

US Patent 6537227, titled "Method and equipment for human-related measuring," was filed on March 2, 2001, and issued on March 25, 2003.

Here's a breakdown of its term adjustments and related applications:

Patent Term Adjustments (PTA) / Patent Term Extensions (PTE):

• Patent Term Adjustment (PTA): PTA is granted to compensate for delays caused by the USPTO during the prosecution of a patent application. For applications filed on or after June 8, 1995, PTA extends the patent's 20-year term from its earliest non-provisional filing date. The provided patent information does not explicitly state if any PTA was granted.
• Patent Term Extension (PTE): PTE is awarded to compensate for delays in obtaining regulatory approval for a patented product or its methods of manufacturing or use. There is no information provided to suggest that US Patent 6537227 received a PTE.

Continuation Applications, Divisional Applications, and Related Family Members:

• Application Number: US09/798,577 (This is the application number for US6537227).
• Priority Date: The priority date for US6537227 is March 7, 2000. This indicates that the application for US6537227 may claim benefit from an earlier-filed application.
• Other Versions: US20010023320A1 is listed as another version, which is typically a patent application publication corresponding to the granted patent.
• Applications Claiming Priority: The patent document lists three applications claiming priority to FI20000522 (filed 2000-03-07): FI20000522, FI114202B, and FI000522. These are Finnish applications and likely represent the foreign priority filing from which US6537227 claims priority under 35 U.S.C. § 119.
• Family Applications: The family includes US09/798,577 (US6537227B2).
• Country Status: Family members include patents/applications in EP, AT, DE, ES, FI, and HK, indicating international counterparts.

The patent was filed after June 8, 1995, so its term is generally 20 years from its earliest effective filing date.

Projected Expiration Date:
The patent's legal status is listed as "Expired - Lifetime, expires 2021-04-19". This expiration date is noted as an "Adjusted expiration" date. Since the current date is April 26, 2026, the patent has already expired.

Defensive Disclosure: US Patent 6537227 Derivatives

Current Date: April 26, 2026

This document describes derivative variations of the core inventive concept of US Patent 6537227, "Method and equipment for human-related measuring." The purpose of this defensive disclosure is to establish prior art, rendering future incremental improvements by competitors obvious or non-novel, based on established principles, known technologies, and logical extensions of the disclosed invention. The core concept of US6537227 is a heart rate measuring arrangement that assesses a person's energy consumption during exercise by combining a measured heart rate parameter with an energy consumption reference value derived from personalized physical performance parameters.

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I. Material & Component Substitution

Derivative 1: Non-Contact Optical HR Measurement with Flexible, Conductive Polymer Electrodes and a Custom RISC-V ASIC

Enabling Description:
This derivative implements the heart rate measuring means (500A-500B) using non-contact optical photoplethysmography (PPG) sensors for continuous heart rate detection from superficial capillaries, integrated into textile. For enhanced signal quality and redundancy, flexible, graphene-infused conductive polymer electrodes, fabricated via additive manufacturing (e.g., 3D printing or electrospinning), are interwoven into the fabric of a garment. These electrodes detect ECG signals, which are then fused with the PPG data using a Kalman filter for robust heart rate parameter extraction. The calculating unit (532) is realized as a low-power, custom-designed Application-Specific Integrated Circuit (ASIC) based on the open-source RISC-V instruction set architecture, specifically optimized for real-time Fourier Transform of physiological signals and execution of neural network inference for energy consumption assessment. The ASIC incorporates specialized hardware accelerators for matrix multiplication and activation functions to efficiently execute pre-trained energy consumption models. Power is supplied by a flexible, thin-film solid-state battery.

graph TD
    A[Wearable Garment with Sensors] --> B{Non-Contact PPG Sensor Array};
    A --> C{Flexible Graphene-Polymer Electrodes};
    B --> D[Signal Acquisition & Pre-processing (Optical)];
    C --> E[Signal Acquisition & Pre-processing (Electrical)];
    D --> F{Kalman Filter / Sensor Fusion Unit};
    E --> F;
    F --> G[Heart Rate Parameter Extraction];
    G --> H{Custom RISC-V ASIC (Calculating Unit)};
    H --> I[Energy Consumption Assessment Model];
    I --> J[Personalized Performance Parameters];
    J --> H;
    H --> K[Output to Presenting Means];
    K --> L[Flexible E-Ink Display];
    L --> M[User];

Derivative 2: Integrated Piezoelectric Energy Harvesting for HR Monitoring with Bio-compatible Textile Electrodes

Enabling Description:
This variation focuses on energy autonomy. The heart rate measuring means (500A-500B) utilizes bio-compatible, silver-nanowire-infused textile electrodes directly woven into moisture-wicking athletic wear. These electrodes provide high fidelity ECG signals. The power source for the entire heart rate measuring arrangement is an integrated piezoelectric energy harvesting system. Lead Zirconate Titanate (PZT) nanofibers, directly synthesized onto the textile substrates, convert kinetic energy from body movements during exercise into electrical energy. This harvested energy charges a supercapacitor bank, which in turn powers the low-power microcontroller-based calculating unit (532) and presenting means (530). The calculating unit performs real-time heart rate analysis and energy consumption assessment, leveraging a pre-calibrated model based on performance parameters. In situations of insufficient kinetic energy, the system gracefully degrades to a lower sampling rate for heart rate measurement.

graph TD
    A[Athlete Movement] --> B[Piezoelectric Nanofiber Array];
    B --> C[AC/DC Rectifier & Power Management];
    C --> D[Supercapacitor Energy Storage];
    D --> E[Power Rail];
    E --> F[Bio-compatible Textile Electrodes (ECG)];
    F --> G[Signal Conditioning & ADC];
    G --> H[Low-Power Microcontroller (Calculating Unit)];
    H --> I[Heart Rate Calculation Module];
    H --> J[Energy Consumption Model (with personalized performance parameters)];
    I --> H;
    J --> H;
    H --> K[Presenting Means (Low-power OLED)];
    K --> E;
    D --- K;

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II. Operational Parameter Expansion

Derivative 3: Ultra-High Frequency HR & Micro-Motion Compensation for Extreme Sport Energy Expenditure in Cryogenic Environments

Enabling Description:
This derivative pushes the operational parameters to extremes. The heart rate measuring arrangement is designed for extreme sports in cryogenic environments (e.g., arctic exploration, high-altitude mountaineering with supplemental oxygen systems). The heart rate information is measured at an ultra-high frequency of 1000 Hz using a multi-lead ECG system with cryogenically stable, flexible carbon-fiber electrodes. A dedicated Inertial Measurement Unit (IMU) with sub-millisecond synchronization to the ECG data captures micro-motion artifacts (e.g., shivering, frostbite tremors) that could otherwise distort HR signals. The calculating unit (532), housed in a hermetically sealed, insulated module, employs advanced digital signal processing (DSP) algorithms to perform wavelet decomposition and adaptive filtering for precise HR parameter extraction, compensating for environmental and physiological noise. The energy consumption assessment model is extended to include factors for thermogenesis and physiological stress response in extreme cold, leveraging performance parameters calibrated under similar environmental conditions (e.g., VO2max at -30°C). The presenting means (530) is a low-temperature tolerant, transflective LCD integrated into a helmet-mounted display, with a simplified interface for quick readability.

graph TD
    A[Cryogenic Environment] --> B[Athlete];
    B --> C[Multi-Lead ECG (1000 Hz)];
    B --> D[IMU (Micro-motion data)];
    C --> E[ECG Signal Conditioning];
    D --> F[Motion Data Processing];
    E --> G{DSP Unit: Wavelet Decomposition & Adaptive Filtering};
    F --> G;
    G --> H[Precise HR Parameter Extraction];
    H --> I[Calculating Unit (Insulated Module)];
    I --> J[Energy Consumption Model (Thermoregulation factors)];
    J --> K[Performance Parameters (Cryogenic-calibrated)];
    K --> I;
    H --> I;
    I --> L[Helmet-Mounted Transflective LCD];
    L --> B;

Derivative 4: Distributed Sensor Network for Team-Based Energy Expenditure Monitoring Across Varying Atmospheric Pressures

Enabling Description:
This system extends to a distributed, team-based monitoring solution operating across diverse atmospheric pressures, from sea level to high altitude. Each athlete wears a compact, robust heart rate monitor that communicates wirelessly via a low-power mesh network (e.g., LoRaWAN). Each individual measuring means (500A-500B) captures heart rate, skin temperature, and localized barometric pressure. The calculating unit (532) is distributed: a local edge processor on each monitor performs initial HR parameter extraction and noise reduction. A central gateway unit aggregates data from multiple athletes. The energy consumption reference values are dynamic, adjusted in real-time by the central calculating unit based on aggregated individual physiological responses and the current atmospheric pressure, accounting for changes in oxygen availability. Performance parameters for each athlete (e.g., maximal aerobic power at different altitudes) are pre-loaded or adaptively updated. The presenting means (530) includes individual displays for immediate feedback, and a central command display providing aggregated team energy expenditure, individual exertion levels, and predicted fatigue metrics, accessible via a tablet or ruggedized laptop.

graph TD
    subgraph Athlete 1
        A1[HR Monitor 1] --> B1[Edge Processor 1]
        B1 --> C1[LoRaWAN Transceiver 1]
    end
    subgraph Athlete 2
        A2[HR Monitor 2] --> B2[Edge Processor 2]
        B2 --> C2[LoRaWAN Transceiver 2]
    end
    subgraph Athlete N
        AN[HR Monitor N] --> BN[Edge Processor N]
        BN --> CN[LoRaWAN Transceiver N]
    end

    C1 --- D[LoRaWAN Gateway];
    C2 --- D;
    CN --- D;
    D --> E[Central Calculating Unit];
    E --> F[Dynamic Energy Consumption Model (Altitude-adjusted)];
    F --> G[Aggregated & Individual Performance Parameters];
    G --> E;
    E --> H[Central Command Display];
    E --> I[Individual Monitor Displays];
    I --> A1;
    I --> A2;
    I --> AN;

---

III. Cross-Domain Application

Derivative 5: Livestock Energy Expenditure Monitoring (AgTech)

Enabling Description:
Applying the core concept to AgTech, this system monitors the energy expenditure of livestock (e.g., cattle, swine) to optimize feed intake, breeding efficiency, and health management. The heart rate measuring means consists of a subcutaneous or surface-mounted bio-impedance sensor for heart rate detection, coupled with an accelerometer to measure activity levels (as a proxy for performance parameters like speed/workload). The sensor data is transmitted wirelessly (e.g., BLE) to a localized herd management hub. The calculating unit processes the animal's heart rate and activity data. Energy consumption reference values are established for different animal types, ages, and physiological states (e.g., lactation, growth) using empirically derived performance parameters (e.g., feed conversion ratio, weight gain rate under specific activity levels). The assessment of energy consumption guides precision feeding protocols. The presenting means is a mobile application or farm management dashboard, displaying individual animal energy budgets, alerts for unusual activity patterns, and herd-level energy expenditure trends.

graph TD
    A[Animal (e.g., Cow)] --> B[Bio-impedance HR Sensor];
    A --> C[Accelerometer (Activity)];
    B --> D[Wireless Transmitter (BLE)];
    C --> D;
    D --> E[Herd Management Hub (Calculating Unit)];
    E --> F[Energy Consumption Model (Animal-specific)];
    F --> G[Performance Parameters (Feed Conversion, Weight Gain)];
    G --> E;
    E --> H[Farm Management Dashboard / Mobile App (Presenting Means)];
    H --> I[Farm Manager];

Derivative 6: Industrial Worker Fatigue Monitoring (Industrial Safety/Human Factors)

Enabling Description:
In an industrial setting, this system monitors a worker's energy expenditure during physically demanding tasks to prevent fatigue-related accidents and optimize work-rest cycles. The heart rate measuring means comprises a chest-strap or smart garment integrated ECG sensor for continuous heart rate measurement. Additional performance parameters are derived from wearable IMUs (e.g., for lifting intensity, repetitive motion count) and environmental sensors (e.g., ambient temperature, humidity). The calculating unit, worn by the worker or integrated into a smart helmet, uses the heart rate and workload-derived performance parameters to assess real-time energy consumption and predict fatigue levels. Energy consumption reference values are established based on individual worker physiology, job role, and specific task demands (e.g., maximum power output for a specific lifting task). The presenting means includes a subtle haptic feedback system on the worker's wrist (e.g., vibrating when fatigue threshold is approached) and a supervisor's dashboard for aggregated team performance and fatigue risk assessment.

graph TD
    A[Industrial Worker] --> B[Smart Garment ECG];
    A --> C[Wearable IMU (Workload)];
    A --> D[Environmental Sensors];
    B --> E[Worker-Worn Calculating Unit];
    C --> E;
    D --> E;
    E --> F[Energy Consumption & Fatigue Model];
    F --> G[Job-Specific Performance Parameters];
    G --> E;
    E --> H[Haptic Feedback (Worker)];
    E --> I[Wireless Link (Site Network)];
    I --> J[Supervisor's Dashboard (Presenting Means)];
    J --> K[Safety Manager];

Derivative 7: Spacecraft Crew Energy Management (Aerospace)

Enabling Description:
For long-duration space missions, this system manages astronaut energy consumption to optimize nutritional intake, exercise regimens, and mission planning, considering microgravity effects. The heart rate measuring means is a non-invasive, body-worn array of electrodes (e.g., integrated into mission attire) that continuously monitors ECG. Performance parameters include microgravity exercise equipment workload data (e.g., treadmill speed, resistance) and integrated spirometry data (for direct oxygen uptake measurement). The calculating unit, a redundant, radiation-hardened embedded system, uses real-time HR and performance parameters to assess energy consumption, applying reference values adjusted for microgravity physiology and long-duration spaceflight (e.g., altered metabolic rates, muscle atrophy effects). The presenting means is an augmented reality (AR) overlay in the astronaut's visor, showing immediate energy status, and a ground control station interface for comprehensive crew health and resource management.

graph TD
    A[Astronaut in Spacecraft] --> B[Mission Attire ECG Array];
    A --> C[Microgravity Exercise Workload Data];
    A --> D[Integrated Spirometry (VO2)];
    B --> E[Redundant Calculating Unit];
    C --> E;
    D --> E;
    E --> F[Energy Consumption Model (Microgravity-adjusted)];
    F --> G[Performance Parameters (Spaceflight-calibrated)];
    G --> E;
    E --> H[Astronaut AR Visor Display];
    E --> I[Telemetry Link (Ground Control)];
    I --> J[Ground Control Station (Presenting Means)];
    J --> K[Mission Control Specialist];

---

IV. Integration with Emerging Tech

Derivative 8: AI-Optimized Adaptive Energy Expenditure Model with Federated Learning & Blockchain-Verified Performance Data

Enabling Description:
This derivative integrates AI, IoT, and blockchain. The heart rate measuring means (500A-500B) consists of an IoT-enabled smart wearable (e.g., ring, patch) that continuously streams raw PPG and accelerometer data via a secure wireless connection. The calculating unit (532) leverages a distributed AI architecture. Initial heart rate parameter extraction and local energy consumption assessment occur on-device using a lightweight federated learning model (e.g., TensorFlow Lite). This model is periodically updated by a central server that aggregates anonymized model weights from a large population of users, ensuring continuous improvement without direct sharing of raw personal data. Performance parameters (e.g., maximal oxygen uptake, lactate threshold) are measured during calibrated reference exercises and are cryptographically hashed and time-stamped onto a permissioned blockchain (e.g., Hyperledger Fabric) as verifiable credentials, enhancing data integrity and user control over their physiological profiles. These blockchain-verified performance parameters are used to refine the individual's energy consumption reference values within the AI model. The presenting means (530) is a multi-modal interface including a smartphone application, smart display, and voice assistant, providing personalized real-time energy expenditure insights and long-term trends.

sequenceDiagram
    participant UserWearable
    participant CentralServer
    participant Blockchain
    participant UserApp

    UserWearable->>CentralServer: Upload anonymized model weights (Federated Learning)
    CentralServer->>CentralServer: Aggregate weights & update global model
    CentralServer->>UserWearable: Download updated AI model
    UserWearable->>UserWearable: Measure HR & Accel data
    UserWearable->>UserWearable: On-device AI for HR & initial EC assessment
    UserWearable->>UserApp: Display real-time EC
    
    UserApp->>UserApp: Perform reference exercise & input results
    UserApp->>Blockchain: Store hashed Performance Parameters (e.g., VO2max)
    Blockchain-->>UserApp: Provide verifiable credential
    UserApp->>UserWearable: Update local AI model with verified PP
    Note over UserWearable,CentralServer: Continuous adaptive learning & assessment

Derivative 9: Real-Time Haptic Feedback System for Personalized Metabolic Pacing via Edge AI & Predictive Analytics

Enabling Description:
This derivative uses advanced human-computer interaction and predictive AI. The heart rate measuring means is an integrated smart fabric sensor array (ECG and respiration rate) embedded in performance apparel, streaming data to a wrist-worn edge device. The calculating unit (532) on the edge device employs an event-driven, low-latency Edge AI model trained with recurrent neural networks (RNNs) to perform predictive analytics of metabolic state. Based on measured heart rate, respiration rate, and dynamically updated performance parameters (e.g., real-time aerobic threshold estimation), the Edge AI calculates instantaneous energy expenditure and predicts a user's metabolic pathway (e.g., fat burning, carbohydrate utilization). Energy consumption reference values are continuously refined using individualized metabolic efficiency coefficients. The presenting means (530) is a sophisticated haptic feedback system, providing subtle, non-distracting physical cues to the user. For instance, varying patterns or intensities of vibration on different parts of the wrist/arm guide the user to maintain an optimal pace for a desired metabolic zone (e.g., a steady, slow vibration for fat-burning, a faster, more intense vibration for high-intensity carbohydrate burning). A small, high-refresh-rate micro-LED display provides secondary visual confirmation.

graph TD
    A[Performance Apparel (ECG & Respiration)] --> B[Wireless Edge Device];
    B --> C[Edge AI Model (RNN)];
    C --> D[HR & Respiration Parameter Extraction];
    C --> E[Dynamic Performance Parameter Update];
    D --> C;
    E --> C;
    C --> F[Predictive Metabolic State Analysis (EC, Fuel Source)];
    F --> G[Personalized Metabolic Pacing Logic];
    G --> H[Haptic Feedback Actuators];
    H --> I[User];
    B --> J[Micro-LED Display];
    J --> I;

---

V. The "Inverse" or Failure Mode

Derivative 10: Fail-Safe, Low-Power Mode for Critical Physiological Monitoring with Simplified Energy Expenditure Assessment

Enabling Description:
This derivative outlines a robust, fail-safe operating mode for situations where primary functionality or full power is compromised, particularly for critical applications (e.g., elderly monitoring, medical recovery). The heart rate measuring means (500A-500B) utilizes a redundant, ultra-low-power optical PPG sensor array, continuously monitored for signal quality and battery voltage. In the event of primary sensor degradation, low battery (below 10% capacity), or a detected fault in the high-fidelity calculating unit, the system automatically transitions to a fail-safe, low-power mode. In this mode, the calculating unit (532) switches to a minimal processing core, reducing its clock frequency and deactivating non-essential modules. It prioritizes continuous heart rate monitoring (with reduced sampling rate, e.g., once every 30 seconds). The energy consumption assessment is significantly simplified, approximating basal metabolic rate (BMR) plus a minimal activity factor (derived from a simple accelerometer threshold), rather than using complex performance parameters or piecewise linear models. The presenting means (530) defaults to a blinking LED indicator for status and a minimal segment display showing only HR and an "LPM" (Low-Power Mode) flag. All data logging is suspended, and only critical alerts (e.g., HR outside safe range) are transmitted to a base station via a periodic, burst-mode radio transmission, maximizing operational time under adverse conditions.

stateDiagram-v2
    [*] --> Normal_Operation
    Normal_Operation --> Low_Power_Mode : Sensor_Degradation OR Low_Battery OR Calc_Unit_Fault
    Low_Power_Mode --> Normal_Operation : Fault_Cleared AND Power_Restored
    Low_Power_Mode --> Critical_Alert : HR_OutOfRange
    Critical_Alert --> Low_Power_Mode : Alert_Acknowledged OR HR_Normal

    state Normal_Operation {
        High_Fidelity_HR_Measurement --> Complex_EC_Assessment
        Complex_EC_Assessment --> Full_Display_Feedback
    }

    state Low_Power_Mode {
        Minimal_HR_Monitoring --> Simplified_EC_Approximation
        Simplified_EC_Approximation --> Blinking_LED_Display
        Blinking_LED_Display --> Burst_Mode_Alert_Transmission
    }

---

Combination Prior Art Scenarios

Here are at least three "Combination Prior Art" scenarios where the core concept of US Patent 6537227 (personalized energy consumption assessment using heart rate and performance parameters) is combined with an existing open-source standard.

1. US6537227 (Core Concept) + Bluetooth Low Energy (BLE) Heart Rate Profile (HRP) / Generic Attribute Profile (GATT) Service:

   • Description: A heart rate measuring arrangement uses a chest strap (transmitter) or optical sensor that collects heart rate data. This heart rate data is then transmitted wirelessly from the measuring means to a calculating unit (e.g., a smartphone, smartwatch, or dedicated receiver unit) using the standardized Bluetooth Low Energy (BLE) protocol, specifically adhering to the Heart Rate Profile (HRP) and its associated GATT service. This open-source standard defines how heart rate measurements are structured and communicated between devices. The calculating unit, after receiving the standardized heart rate parameter, combines it with personalized energy consumption reference values derived from performance parameters (e.g., maximal oxygen uptake, running speed) to assess energy consumption during exercise, as per US6537227. The assessment is then presented on a display or application.
   • Technical Justification: BLE HRP (adopted by the Bluetooth SIG) is a widely used and openly specified standard for transmitting heart rate data from sensors. Combining this standard data transmission method with US6537227's novel calculation method is an obvious integration for any implementer aiming for interoperability and ease of adoption. A PHOSITA would readily recognize the benefit of using an industry-standard communication protocol for the heart rate data input to the calculation.

2. US6537227 (Core Concept) + TensorFlow Lite for On-Device AI Models:

   • Description: The calculating unit (532) in a heart rate measuring arrangement incorporates a machine learning model, specifically a neural network as described in US6537227 (FIG. 3, 4A, 4B) for forming performance parameter values (MM-I 300) or for assessing energy consumption (MM-2 302). This neural network model is implemented using TensorFlow Lite, an open-source machine learning framework designed for on-device inference at the edge. The physiological parameters, heart rate parameters, and/or exercise stress parameters (e.g., age, weight, heart rate frequency, workload) are fed into the TensorFlow Lite model. The model outputs performance parameters (e.g., estimated VO2max) or directly calculates an energy consumption assessment. The energy consumption reference values, derived from these performance parameters, are then used with the real-time heart rate parameter to refine the energy consumption assessment, as taught by US6537227.
   • Technical Justification: TensorFlow Lite is an openly available, optimized framework for deploying machine learning models on resource-constrained devices, such as those typically found in heart rate monitors or wearables. Given US6537227's explicit mention of neural networks for assessment, a PHOSITA would find it obvious to use a leading open-source framework like TensorFlow Lite to implement such models, especially for optimizing performance and battery life on embedded systems.

3. US6537227 (Core Concept) + MQTT (Message Queuing Telemetry Transport) for IoT Data Aggregation:

   • Description: In a scenario where multiple heart rate measuring arrangements (e.g., for a sports team or a fitness center) are deployed, the raw heart rate information and the calculated energy consumption assessments are transmitted from individual devices to a central server or cloud platform. This data transmission is performed using the MQTT protocol, an open-source, lightweight, publish-subscribe network protocol ideal for IoT communication. Each heart rate monitor publishes its heart rate parameter and local energy consumption assessment to specific MQTT topics. A central calculating unit subscribes to these topics, aggregates the data, and further refines personalized energy consumption profiles by cross-referencing with more comprehensive performance parameters stored centrally. The presenting means (530) then displays aggregated and individual energy consumption data via a web dashboard that receives updates from the MQTT broker.
   • Technical Justification: MQTT is an OASIS standard and widely adopted open-source protocol for efficient data exchange in IoT environments, characterized by its minimal overhead and ability to handle unreliable networks. For scaling the US6537227 system beyond a single user to a multi-device or cloud-integrated solution, it would be an obvious choice for a PHOSITA to leverage an established IoT communication standard like MQTT for robust and efficient data aggregation, enabling broader data analysis and presentation capabilities.