Obviousness

Obviousness Analysis of US Patent 8989441 under 35 U.S.C. § 103

To determine the obviousness of US Patent 8989441, we consider whether the claimed invention as a whole would have been obvious to a person having ordinary skill in the art (POSITA) at the time of the invention (the filing date of March 18, 2013), given the prior art. Obviousness requires identifying a motivation to combine prior art references to arrive at the claimed invention with a reasonable expectation of success. A POSITA is a hypothetical person with average knowledge and expertise in the relevant technical field.

The invention broadly concerns a data acquisition method and device for motion recognition, wherein an initial recognition module in a data acquisition device identifies a motion trigger point and stores a predefined range of motion data around this point, which is then transmitted to a motion computing device. This aims to reduce wireless transmission pressure and power consumption while maintaining accuracy.

Prior Art References

The following prior art references are cited in US8989441B2:

• US6289124B1 (Sanyo Electric Co., Ltd.): "Method and system of handwritten-character recognition." This patent, filed April 27, 1998, and issued September 11, 2001, describes a method and system for handwritten character recognition. While not directly related to sports motion, it deals with sensor data acquisition and recognition.
• US20050259739A1 (Sony Corporation): "Image processing apparatus and method, and recording medium and program used therewith." This application, filed April 9, 2004, and published November 24, 2005, focuses on image processing for various applications. It suggests technologies for analyzing visual data.
• WO2011003218A1 (Zheng Han): "Acceleration motion identify method and system thereof." Published January 13, 2011, this international application by one of the inventors of US8989441B2 describes a method and system for identifying acceleration motion. This is highly relevant as it addresses motion identification using acceleration data.
• CN102591445A (Shenzhen Hezhisheying Electronic Co., Ltd.): "Stress sensing simulation method and equipment." Published July 18, 2012, this Chinese application relates to stress sensing and simulation.
• CN102221369A (Zheng Han): "Gesture recognizing method and device of ball game and gesture auxiliary device." Published October 19, 2011, this Chinese application, also by one of the inventors, specifically addresses gesture recognition in ball games and a corresponding auxiliary device. This is highly relevant as it directly pertains to sports motion recognition using sensors.

Obviousness Combinations and Rationales

A conclusion of obviousness can be supported by rationales such as combining prior art elements according to known methods to yield predictable results, or using a known technique to improve similar devices. The motivation to combine can be found explicitly or implicitly in market forces, design incentives, or a known problem in the field.

Combination 1: WO2011003218A1 + CN102221369A + General Knowledge of Data Transmission Optimization

• WO2011003218A1 discloses an acceleration motion identification method and system. This reference teaches the fundamental aspects of collecting and identifying motion based on acceleration data.

• CN102221369A describes a gesture recognizing method and device specifically for ball games, using an auxiliary device. This shows the application of motion recognition to sports equipment. The problem of transmitting large amounts of sensor data in real-time over wireless channels, leading to high power consumption and channel pressure, is a known challenge in motion recognition systems that use high sampling rates. The background section of US8989441B2 explicitly states this problem: "in the case of a high sampling rate, the huge amount of data collected by the sensor will exert too much pressure on the transmission over the wireless channel. This not only results in large wireless power consumption, but also goes beyond the maximum capacity of the wireless channel."

• Motivation to Combine: A POSITA in the field of motion recognition systems would be motivated to combine the motion identification techniques of WO2011003218A1 and the sports-specific application of CN102221369A with common knowledge of data transmission optimization to address the aforementioned problem of excessive data transmission. The goal would be to improve efficiency and reduce power consumption in wireless sensor-based systems. It is a known technique to reduce data transmission by filtering or pre-processing data at the source when only specific events or relevant data segments are of interest for further analysis.

  • Resulting Obviousness: A POSITA would find it obvious to implement an "initial recognition module" in the data acquisition device (as described in claims 1 and 9 of US8989441B2) to perform preliminary processing. This module would identify "motion trigger points" (e.g., impacts in a ball game as suggested by CN102221369A) and only transmit data around these significant events. Storing a "predefined range" of data (m*Fs frames before, the trigger point, and n*Fs-1 frames after) in a "data storage module" for subsequent transmission via a "communications module" to a "motion computing device" (as detailed in claims 1, 9, and 17) would be a predictable solution to reduce the volume of transmitted data. This is a known technique to improve similar devices (motion recognition systems) in the same way (by optimizing data transmission).

Combination 2: US6289124B1 + WO2011003218A1 + CN102221369A

• US6289124B1 describes a method and system for handwritten character recognition using sensors to acquire data. While a different application, it establishes the concept of a "data acquisition device comprising a sensor" performing initial recognition and processing for subsequent transmission for a more complex recognition task.

• WO2011003218A1 provides a method and system for acceleration motion identification.

• CN102221369A discloses a gesture recognizing method and device for ball games, making it clear that motion data from sensors can be used for sports analysis.

• Motivation to Combine: A POSITA would be motivated to adapt the data acquisition and initial recognition principles from US6289124B1 (general sensor data processing for recognition) to the specific context of motion recognition in sports, as taught by WO2011003218A1 and CN102221369A. The motivation would be to enhance the efficiency of sports motion recognition systems by intelligently managing sensor data, similar to how handwritten character recognition systems might focus on significant strokes. The challenge of processing and transmitting all raw sensor data for accurate recognition would be apparent to a POSITA.

  • Resulting Obviousness: It would be obvious to apply the concept of an initial recognition step at the data acquisition device (as shown in US6289124B1 for handwritten characters) to motion data in a sports context (WO2011003218A1, CN102221369A). This would involve detecting a "motion trigger point" (analogous to a significant part of a character stroke) and only transmitting a "predefined range" of data around that point, thus addressing the efficiency and bandwidth concerns inherent in wireless data transmission for real-time sports analysis. The system and method claims (1, 9, 17) of US8989441B2 would be rendered obvious by this combination.

Combination 3: US20050259739A1 + WO2011003218A1 + CN102221369A

• US20050259739A1 pertains to image processing, including methods for acquiring and processing data for recognition. While image-based, it highlights the concept of processing raw input (image data) to extract relevant information for further recognition by a separate computing device.

• WO2011003218A1 and CN102221369A clearly demonstrate the application of sensor-based motion data for recognition in sports.

• Motivation to Combine: A POSITA would recognize that the principle of pre-processing or "initial recognition" of data at the acquisition stage (as seen in image processing with US20050259739A1) could be beneficially applied to sensor-based motion data for sports. The motivation would be to reduce the computational load on the main "motion computing device" and optimize data transmission from the "data acquisition device" by sending only pertinent segments of motion data. This is a common problem-solving strategy in data-intensive applications.

  • Resulting Obviousness: Applying an initial recognition step to identify and isolate key motion events (trigger points) in sensor data for sports (as taught by WO2011003218A1 and CN102221369A), mirroring the data reduction techniques in image processing (US20050259739A1), would be obvious. The specific mechanism of storing m*Fs frames before and n*Fs-1 frames after the trigger point for transmission is a predictable design choice for capturing the full context of the event while minimizing overall data. Thus, the method, device, and system claims (1, 9, 17) of US8989441B2 would be obvious.

In summary, the core inventive step of US8989441B2 – pre-processing motion data at the acquisition device to extract and transmit only data around a motion trigger point to a separate computing device for full recognition – addresses a known problem of wireless data transmission efficiency and power consumption. The individual elements of sensor-based motion recognition, initial data processing, and segmented data transmission were present in the prior art, particularly in related fields or even by the same inventors. A POSITA would have been motivated to combine these known elements to achieve the predictable result of improved efficiency in sports motion recognition systems.