Apple inc. (20240099627). FORCE ESTIMATION FROM WRIST ELECTROMYOGRAPHY simplified abstract
Contents
- 1 FORCE ESTIMATION FROM WRIST ELECTROMYOGRAPHY
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 FORCE ESTIMATION FROM WRIST ELECTROMYOGRAPHY - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Unanswered Questions
- 1.11 Original Abstract Submitted
FORCE ESTIMATION FROM WRIST ELECTROMYOGRAPHY
Organization Name
Inventor(s)
Matthias R. Hohmann of Mountain View CA (US)
Ellen L. Zippi of Daly City CA (US)
Kaan E. Dogrusoz of San Francisco CA (US)
FORCE ESTIMATION FROM WRIST ELECTROMYOGRAPHY - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240099627 titled 'FORCE ESTIMATION FROM WRIST ELECTROMYOGRAPHY
Simplified Explanation
The patent application describes improved techniques for estimating muscular force using surface electromyography (EMG) measurements, potentially worn on a wrist. The estimate is based on variations between voltage measurements and spectral properties of the measurements, which can be used for hand gesture recognition and health metrics.
- Single-channel or multiple-channel surface electromyography (EMG) measurements
- Measurement device worn on a wrist
- Muscular force estimate based on variation between adjacent voltage measurements and spectral properties
- Improved hand gesture recognition and health metrics for the user
Potential Applications
The technology could be applied in various fields such as healthcare, sports performance monitoring, rehabilitation, and human-computer interaction.
Problems Solved
The technology addresses the challenge of accurately estimating muscular force, which is crucial for applications like rehabilitation and sports performance monitoring.
Benefits
The benefits of this technology include improved accuracy in estimating muscular force, enhanced hand gesture recognition, and better health metrics for the user.
Potential Commercial Applications
Potential commercial applications of this technology could include wearable devices for fitness tracking, rehabilitation tools, and gesture-controlled devices.
Possible Prior Art
One possible prior art could be existing EMG-based devices for muscle force estimation or gesture recognition, but the specific techniques described in this patent application may offer improvements in accuracy and usability.
Unanswered Questions
How does this technology compare to existing EMG-based devices for muscle force estimation?
The article does not provide a direct comparison to existing EMG-based devices for muscle force estimation, so it is unclear how this technology differs in terms of accuracy, usability, and other factors.
What are the potential limitations or challenges of implementing this technology in real-world applications?
The article does not address potential limitations or challenges of implementing this technology in real-world applications, such as cost, user acceptance, or technical constraints.
Original Abstract Submitted
aspects of the subject technology provide improved techniques for estimating muscular force. the improved techniques may include single-channel or multiple-channel surface electromyography (emg), such as via a measurement device worn on a wrist. a muscular force estimate may be based on one or more measurements of variation between adjacent voltage measurements and estimates of spectral properties of the voltage measurements. the resulting muscular force estimate may for a basis for improved hand gesture recognition and/or heath metrics of the user.
