(269 days)
Surface Electromyography with range of motion functional capacity assessment grip and pinch strength.
The Intended Use Section is identical to the original device PMRU (K022719) To provide non-invasive muscle testing integrating with range of motion, functional capacity of lifting, pulling, pushing, pinching and gripping. To pinpoint muscle activity during movement objectively isolating abnormal movements with abnormal muscle patterns. To establish relative functioning of muscle in any specific anomaly that may occur due to muscle damage, muscle fatigue, hypertonicity or stress. To pinpoint referred pain pattern associated with cervical, thoracic, lumbosacral upper and lower extremities, and refer pain sources. To evaluate a baseline muscle activity for preemployment screening, sport medicine. To look at chronic vs. acute muscle function and range of motion to ascertain good effort with FCE, range of motion, and gripping, and pinch. To ascertain the ischemic activity of muscles. To ascertain chronic damage to muscles. To monitor the frequency range for cardiac muscle.
The Physical Monitoring Registration Unit-S, (PMRU-S) like the legally cleared PMRU combines surface EMG with functional capacity sensors range of motion, grip and pinch strength sensors. This integration allows for a reproducible, objective interpretation of muscle function and effort via the range of motion, fce, pinch and grip. All muscle groups of the body from cervical (to mid back, low back and extremities can be monitored with the device). Bilateral muscle testing is done to compare antagonist muscle groups. The devices monitors bilateral muscle activity with the force produced by the patient while he or she pulls on the strain gauge, with the range of motion. is to provide non-invasive muscle testing integrating with range of motion, functional capacity of lifting, pulling, pushing, pinching and gripping. To measure surface emg along the spine, extremities or cervical region. To measure the EMG with functional tasks, to measure the EMG with range of motion, to measure the EMG with pinch and or grip. This this is identical to the already cleared PMRU.
Here's an analysis of the provided text regarding the PMRU-S device, focusing on acceptance criteria and supporting studies:
It's important to note that the provided document is a 510(k) Summary for substantial equivalence, not a detailed clinical study report. Therefore, some information, particularly regarding specific performance metrics and detailed study methodologies, might be summarized or omitted in comparison to a full scientific publication.
Acceptance Criteria and Device Performance
The document doesn't explicitly state quantitative acceptance criteria or a specific study designed to prove the device meets these criteria in a broad sense. Instead, it focuses on demonstrating substantial equivalence to a predicate device (PMRU K022719). The primary "acceptance criteria" presented are implied through this comparison, meaning the PMRU-S must perform at least as well as the predicate device in its fundamental functions.
The validation testing described focuses on accuracy and repeatability of individual sensor components.
Implied Acceptance Criteria and Reported Device Performance (Based on Substantial Equivalence and Validation Testing)
| Acceptance Criteria (Implied) | Reported Device Performance |
|---|---|
| Functional Equivalence: Same intended use as predicate (PMRU). | "PMRU-S has the same intended use as the predicate" |
| Technological Equivalence: Same fundamental technological characteristics as predicate (PMRU) for core functionalities (EMG, strain gauge, grip, pinch sensors). | "The PMRU-S uses all the same technological characteristics, it uses the same strain gage, grip, pinch and EMG sensors." |
| Differences are: data transmission (Bluetooth vs. USB/PCMCI), power source (battery vs. 110V AC), and DAQ location (in each sensor vs. main circuit board). These changes are asserted not to alter fundamental scientific technology or safety/efficacy. | |
| EMG Sensor Accuracy and Repeatability | "It was show [shown] through validation using... Signal Generator for EMG Sensors. It was shown through this validation testing that all sensors captured data accurately and repeatability." |
| Range of Motion Sensor Accuracy and Repeatability | "It was show [shown] through validation using... inclinometer testing for Range of Motion... It was shown through this validation testing that all sensors captured data accurately and repeatability." |
| FCE (Functional Capacity Evaluation) Sensor Accuracy and Repeatability | "It was show [shown] through validation using weights for FCE... It was shown through this validation testing that all sensors captured data accurately and repeatability." |
| Pinch Strength Sensor Accuracy and Repeatability | "It was show [shown] through validation using weights for... Pinch... It was shown through this validation testing that all sensors captured data accurately and repeatability." |
| Grip Strength Sensor Accuracy and Repeatability | "It was show [shown] through validation using weights for... Grip... It was shown through this validation testing that all sensors captured data accurately and repeatability." |
| Electrical Safety/EMC: Conformity to 60601 standard. | "Both PMRU and PMRU-s conform to 60601." |
Study Details
The document describes validation tests rather than a traditional clinical study with human subjects, given that the changes are primarily related to wireless data transmission and power.
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Sample size used for the test set and the data provenance:
- The document does not specify a sample size for the "validation tests." It refers to "weights" for FCE, Pinch, and Grip, "inclinometer testing" for Range of Motion, and a "Signal Generator" for EMG. This suggests a laboratory-based testing environment with physical standards or simulated inputs, not a human patient test set.
- Data Provenance: Not explicitly stated, but the nature of the tests (using signal generators, weights, inclinometers) suggests it was in-house (e.g., at the manufacturer's facility) and not from human subjects in a clinical setting. It would be considered prospective as it was conducted specifically for this submission.
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Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- Not applicable. The "ground truth" for these validation tests was established by objective physical standards (e.g., known weights, known angles from an inclinometer, specified signals from a signal generator). Human experts were not involved in establishing this type of ground truth.
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Adjudication method for the test set:
- Not applicable. Since the ground truth was based on objective physical standards, there was no need for human expert adjudication. The device's measurements would be compared directly to the known values of the standards.
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If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:
- Not applicable. This device (PMRU-S) is a diagnostic measurement tool (EMG, ROM, strength) and not an AI-powered image analysis or diagnostic support system that would typically be evaluated with an MRMC study involving human readers.
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If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
- Yes, implicitly. The validation tests described (using signal generators, weights, inclinometers) represent a form of standalone performance evaluation, as they assess the sensor's ability to accurately capture physical parameters without human interpretation of the device's output in a diagnostic context. The device itself (the sensors and data acquisition) is being tested in a "standalone" fashion against known inputs.
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The type of ground truth used:
- Physical Standards/Calibration References: Known weights for FCE, Pinch, and Grip; inclinometer readings for Range of Motion; and signal generator outputs for EMG.
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The sample size for the training set:
- Not applicable. This device is described as operating on established physical principles (EMG, strain gauges) and is demonstrating equivalence to a predicate. There is no mention of machine learning or AI algorithms that would require a "training set" in the conventional sense. The device's calibration and underlying algorithms would likely have been developed and tested on previous data, but not in the context of a "training set" for this specific 510(k) submission.
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How the ground truth for the training set was established:
- Not applicable for the reasons outlined in point 7.
§ 890.1375 Diagnostic electromyograph.
(a)
Identification. A diagnostic electromyograph is a device intended for medical purposes, such as to monitor and display the bioelectric signals produced by muscles, to stimulate peripheral nerves, and to monitor and display the electrical activity produced by nerves, for the diagnosis and prognosis of neuromuscular disease.(b)
Classification. Class II (performance standards).