Search Results

Surface electromyography with video recording, range of motion tracking, isometric functional testing and pinch and grip strength measuring.

The CMAP Pro™ is a stand-alone, battery operated dynamic muscle function monitoring system, with a number of surface electromyography (sEMG) sensors connected to various parts of the subject's body for data collection. The data are then directly fed into a system for conditioning, acquiring, and transmitting sensor data. Analyzed signals include sEMG readings, motion detection, and muscle strength measurements. The system acquires continuous analog signals and then digitizes these signals by sampling at a rate of 2kHz. These data are then transferred wirelessly to an all-in-one PC for processing using software.. The system is capable of monitoring and video recording data from (SEMG) sensors connected to various muscle groups in the human body. During the acquisition of sEMG signals, the system will simultaneously acquire motion tracking of the body, isometric functional testing and pinch and grip strength measuring.

Here's a breakdown of the acceptance criteria and study information for the CMAP Pro™ device, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size for the Test Set and Data Provenance

The provided text does not specify the sample size used for the test set or the data provenance (e.g., country of origin, retrospective/prospective). It only mentions "validation tests were performed."

3. Number of Experts Used to Establish Ground Truth and Qualifications

The provided text does not specify the number or qualifications of experts used to establish ground truth for the test set.

4. Adjudication Method for the Test Set

The provided text does not specify any adjudication method used for the test set.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

The provided text does not mention a Multi-Reader Multi-Case (MRMC) comparative effectiveness study, nor does it provide information on the effect size of human readers improving with AI vs. without AI assistance. The CMAP Pro™ is described as a diagnostic device, not one that directly assists human readers in interpreting images or data in an "AI-assisted" context. Its comparisons are against a previous version of the company's own device.

6. Standalone Performance Study (Algorithm Only)

Yes, a standalone performance evaluation was conducted for the device's components. The document states:

• "validation tests were performed to validate the accuracy and repeatability of the range of motion (ROM) sensors, the FCE sensor, and the EMG leads."
• "It was shown through the validation tests that the ROM sensors, FCE sensor, and EMG test leads captured data accurately and repeatably."

This indicates that the device's ability to accurately and repeatably acquire data was tested independently of a human operator making interpretations. The "algorithm only" aspect would refer to the device's internal processing and measurement capabilities.

7. Type of Ground Truth Used

The ground truth used for performance testing was likely:

• Reference measurements/standards for accuracy and repeatability: For the ROM, FCE, and EMG leads, the validation would have involved comparing the device's measurements against established, more precise, or gold-standard methods or known physical properties to determine accuracy and consistency (repeatability).

The text doesn't specifically use terms like "expert consensus" or "pathology," but rather implies instrumental validation against known benchmarks or highly accurate measurement techniques.

8. Sample Size for the Training Set

The provided text does not specify the sample size for any training set. Given that this is a 510(k) for a hardware-based diagnostic electromyograph, and not an AI/machine learning algorithm, the concept of a "training set" in the context of machine learning is unlikely to apply in the same way. The device's functionality is based on direct signal acquisition and processing, not learning from a dataset.

9. How the Ground Truth for the Training Set Was Established

As noted above, the concept of a "training set" as typically understood in machine learning is not explicitly applicable or mentioned for this device. Therefore, the method for establishing ground truth for a training set is not provided. The validation focused on the intrinsic performance of the sensors and data acquisition.

Ask a specific question about this device