Obviousness

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.