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510(k) Data Aggregation
(57 days)
The intended use of the Sonic Palpometer is to assess patient sensitivity to tactile stimulus by providing quantification of fingertip pressure, for tactile response procedures and freatments that use digital palpation.
The Palpometer is a simple device that combines the fine motor and sensory attributes of manual examination with the precision measurements made with pressure gauges. By measuring the amount of pressure between the device and a soft tissue, the Palpometer standardizes pain response by controlling the pressure of the examiner's palpating finger. The Palpometer consists of a thin sensor, positioned on the palpating portion of the examiner's finger. The sensor changes its electrical resistance caused by varying the pressure exercised by the examining finger. The Palpometer beeps in a different tone as you pass through each programmable pressure threshold (of which there are five).
The Palpometer is a device designed to quantify fingertip pressure during digital palpation to assess patient sensitivity to tactile stimuli. The provided documentation (K060125) describes the device and references several studies to demonstrate its equivalence and performance relative to conventional pain measurement methods.
Here's an analysis of the acceptance criteria and the studies mentioned:
1. Table of Acceptance Criteria and the Reported Device Performance
The submission does not explicitly state formal "acceptance criteria" with specific quantitative thresholds that the device must meet for approval. Instead, it presents a summary of "Substantial Equivalence Data" by comparing the Palpometer's performance with established methods of pain measurement found in published literature. The reported performance focuses on correlations, reliability, and differences in statistical significance.
| Acceptance Criteria (Inferred from study outcomes and comparisons) | Reported Device Performance (as described in the studies cited) |
|---|---|
| Intraobserver reliability (compared to conventional methods) | Atkins et al. (1992): Intraobserver error of 0.12 for Palpometer vs. 0.2 for conventional method (in rheumatoid arthritis tender joint scores), indicating superior reliability. |
| Construct Validity / Correlation with conventional measurements (indicating agreement or ability to measure the same underlying construct) | Atkins et al. (1992): Correlation coefficient between Palpometer and conventional measurements increased from 0.62 to 0.78 (excluding less sensitive instruments), indicating a high level of construct validity. |
| Interobserver agreement/reliability (demonstrating consistency across different observers) | Bendtsen et al. (1995): Sum of tenderness scores by two observers using conventional palpation differed significantly (P=0.0003), while results did not differ using pressure-controlled palpation (P=0.89), demonstrating improved interobserver reliability with the Palpometer. |
| Correlation with pain intensity (demonstrating the device's ability to measure pain) | Bendtsen et al. (1995): Positive linear correlation between pressure and pain intensity (P=0.00006) in headache tender point scores. |
| Correlation with conventional scores / Test-retest reliability (in specific conditions like fibromyalgia) | Bennet et al. (1996): Good correlation (point estimates >0.7) between Palpometer and conventional scores in fibromyalgia. Test-retest measurements showed similar correlation (>0.7), indicating good reliability. |
| Ability to show a linear relationship between pressure and pain (as expected in controls) | Bendsten et al. (1997): In controls, a linear relationship between pressure and pain was found in a double logarithmic plot (slope (ß) was 3.5 ± 0.66 log mm/log Uj P<0.00001), consistent with expected physiological response. |
| Similar responses to conventional dolorimeters (demonstrating comparable measurement capabilities) | Neufeld et al. (2000): Similar responses before and after manipulation of cranial muscles with Dolorimeter threshold measurements and tenderness measurement with the Palpometer in headache-prone patients. (See Fig 3 & 4 in original paper). |
| Calibration capability with standard dolorimeters (demonstrating quantitative measurement potential) | Bendtsen et al. (1994): A pressure algometer (Somedic) was used to relate arbitrary units of the Palpometer to tone, effectively calibrating the Palpometer against a standard dolorimeter. |
| Construct Validity demonstrated by similar response to tender point measurements with dolorimeter and reproducibility (comparable to other established devices/methods) | Puttick et al. (1995): Construct Validity is demonstrated by similar response to tender point measurements with the dolorimeter at highly reproducible measurements with Palpometer, showing lesser but still good reliability (in fibromyalgia). Atkins and Zielinski (1997) comment: Highlighted that inconsistency in technique and failure to secure the sensor could lead to sub-optimal performance, implying proper use achieves good results. |
2. Sample Sizes Used for the Test Set and the Data Provenance
The document references several published research papers and abstracts rather than a single dedicated test set for the FDA submission. Therefore, the sample sizes and data provenance vary across the cited studies:
- Atkins, C. J. et al. (1992): "An electronic method for measuring joint tenderness in rheumatoid arthritis."
- Sample Size: Not specified in the provided summary, would require consulting the original paper.
- Data Provenance: Not specified in the provided summary (likely prospective, clinical study as typical for such research).
- Bendtsen, L., Jensen, R., Jensen, N.K. and Olesen, J.R. (1995): "Pressure controlled palpation: A new technique which increases the reliability of manual palpation."
- Sample Size: Not specified in the provided summary, would require consulting the original paper.
- Data Provenance: Not specified in the provided summary (likely prospective, clinical study).
- Bennet, R., Atkins, C.J., Zielinski, A., and Makosinski, A. (1996): "A miniaturized pain-measuring device called an electronic Palpometer worn on the examiner's finger links a pressure gauge to conventional manual palpation."
- Sample Size: Not specified in the provided summary, would require consulting the original abstract/paper.
- Data Provenance: Collaborative study between University of Victoria (Canada) and Oregon Health Sciences University (USA). Likely prospective.
- Bendsten, L., Norregaard, J., Jensen, R., Olesen, J. (1997): "Evidence of qualitatively altered nociception in patients with fibromyalgia."
- Sample Size: Not specified in the provided summary, would require consulting the original paper.
- Data Provenance: Not specified in the provided summary (likely prospective, clinical study).
- Neufeld, J.D., Holroyd, K.A., and Lipchik, G.L. (2000): "Dynamic assessment of abnormalities in central pain transmission and modulation in tension-type headache sufferers."
- Sample Size: Not specified in the provided summary, would require consulting the original paper.
- Data Provenance: Not specified in the provided summary (likely prospective, clinical study).
- Bendtsen, L., Jensen, R., Jensen, N.K. and Olesen, J.R. (1994): "Muscle palpation with controlled finger pressure: New equipment for the study of tender myofascial tissues."
- Sample Size: Not specified in the provided summary, would require consulting the original paper.
- Data Provenance: Not specified in the provided summary (likely prospective, clinical study).
- Puttick, M.P.E., et al. (1995): "Reliability and reproducibility of fibromyalgic tenderness: measurement by electronic and mechanical dolorimeters."
- Sample Size: Not specified in the provided summary, would require consulting the original paper.
- Data Provenance: Not specified in the provided summary (likely prospective, clinical study).
- Atkins, C.J., and Zielinski, A. (1997): "Comment on Article by Puttick, M.P.E., et al."
- Sample Size: N/A (commentary on a previous study).
- Data Provenance: N/A (commentary).
3. Number of Experts Used to Establish the Ground Truth for the Test Set and the Qualifications of Those Experts
The concept of "ground truth" in these studies is primarily clinical observation and assessment by human examiners, often involving measurement techniques (conventional palpation, other dolorimeters, VAS scores). The studies focus on comparing the Palpometer's measurements to these human-derived "ground truths" or benchmarks.
- The studies often involve "observers" or "examiners" (e.g., "two different observers" in Bendtsen et al. 1995).
- The qualifications of these experts are not explicitly stated in the summary, but they are implied to be medical professionals (e.g., those experienced in rheumatoid arthritis, headache, or fibromyalgia assessment) contributing to clinical research published in medical journals. Without access to the full papers, specific qualifications (e.g., "radiologist with 10 years of experience") cannot be determined.
4. Adjudication Method for the Test Set
The provided summaries of the studies do not explicitly detail adjudication methods for disagreements between observers.
- Bendtsen et al. (1995) does note that "the sum of tenderness scores recorded by two different observers using conventional palpation differed significantly (P=0.0003) where results did not differ using pressure controlled palpation (P=0.89)." This implies a comparison of agreement rather than a formal adjudication process to resolve discrepancies, likely using statistical methods.
- Other studies focus on correlations and reliability metrics, which inherently account for agreement/disagreement without necessarily requiring a separate adjudication step to define a single "ground truth."
5. 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
- No, a MRMC comparative effectiveness study was not done in the context of an AI-assisted interpretation versus unassisted human interpretation.
- The Palpometer itself is a diagnostic tool that standardizes the human act of palpation, providing objective pressure measurements. It is not an AI algorithm that assists in interpretation of medical images or data.
- The studies instead compare the Palpometer-assisted palpation method to conventional manual palpation or other dolorimeters.
- Effect Size Example: In Atkins et al. (1992), the Palpometer reduced intraobserver error from 0.2 (conventional) to 0.12, and increased the correlation coefficient from 0.62 to 0.78. This indicates an improvement in objective measurement and reliability when using the device compared to unassisted manual palpation.
6. If a Standalone (i.e. algorithm only without human-in-the-loop performance) was Done
- Not applicable. The Palpometer is a human-in-the-loop device. It is designed to be worn on an examiner's finger to quantify the pressure they apply during palpation. It does not operate as a standalone algorithm without human interaction. Its function is to enhance and standardize the human examination process.
7. The Type of Ground Truth Used
The "ground truth" in these studies is primarily established through:
- Expert Clinical Assessment / Conventional Measurements: This includes traditional manual palpation scores, tender joint scores, tender point scores, and Visual Analog Scale (VAS) scores for pain.
- Other Standardized Measurement Devices: Comparisons are made to other dolorimeters and algometers (e.g., Pressore Monitor, micro-emed-system, Dynatron 2000, Somedic pressure algometer, Chatillon dolorimeter). These devices are themselves established as tools for quantifying pressure or pain thresholds.
- Physiological Relationships: For example, the discovery of a "linear relationship between pressure and pain in a double logarithmic plot" (Bendsten et al., 1997) serves as a biological ground truth expectation against which the device's measurements are validated.
8. The Sample Size for the Training Set
- Not applicable / Not explicitly defined. The Palpometer is a hardware device with an embedded microprocessor and programmed thresholds. It does not appear to use machine learning or AI that would require a "training set" in the conventional sense for an algorithm.
- The "programming" of its five pressure thresholds would likely be based on engineering specifications and potentially clinical input, but not iterative learning from a large "training set" of data.
9. How the Ground Truth for the Training Set Was Established
- Not applicable. As explained above, there is no conventional machine learning "training set" for an algorithm. The device's operational parameters (e.g., pressure thresholds for different tones) would be established through engineering design, calibration against known physical pressures, and potentially clinical validation relating these pressure levels to clinically relevant palpation forces.
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