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510(k) Data Aggregation
(86 days)
ACTIWATCH-SCORE
The Actiwatch-Score® is a compact, lightweight, wrist-worn activity monitor that can be used to analyze circadian rhythms, automatically collect and analyze data for sleep parameters, and assess activity in any instance where quantifiable analysis of physical motion is desirable. In addition, the Actiwatch-Score® has a built-in score pad that allows the subject to subjectively assign and enter a score from 0 to 9. The score pad can be used as a substitute or in addition to the traditional patient diary used in conjunction with activity monitoring.
The Actiwatch-Score® is a compact, wrist-worn, battery-operated activity monitor whose physical characteristics are similar to a small wristwatch. The monitor consists of the activity monitor itself and a disposable wrist band. The Actiwatch-Score® is intended for the measurement, storage, and analysis of body activity. The Actiwatch-Score® can be attached to the subject's limb and through the use of an accelerometer, motion of that limb is measured, the activity stored within the activity monitor. A computer program is used to set up the Actiwatch-Score® to collect data. This program is called Actiware-Sleep and runs on an IBM-compatible personal computer (PC). The major functions of Actiware-Sleep are to create a patient score schedule, program the device to collect data, retrieve the data from the activity monitor, display the data, and to store the data for future reference and comparison. The Actiwatch® Reader is a compact interface device that provides a communications link between the Actiwatch-Score® and the PC. The Actiwatch® Reader is connected to the serial communications port of the PC via a standard 9-conductor RS-232 cable. The Actiwatch-Score® utilizes a motion sensor known as an "accelerometer" to monitor the occurrence and degree of motion. This type of sensor integrates the amplitude and speed of motion and produces a small signal whose magnitude and duration depend on the amount of motion. The activity signals are amplified and digitized by the on-board circuit. This information is stored in memory on board the device as activity counts. In addition, the patient self-score data are stored as integer values within memory.
Acceptance Criteria and Study for Actiwatch-Score®
Here's an analysis of the provided text regarding the acceptance criteria and supporting studies for the Actiwatch-Score® device:
1. Table of Acceptance Criteria and Reported Device Performance:
The document describes two key performance aspects for the Actiwatch-Score® related to its new "score" feature:
Parameter | Acceptance Criteria | Reported Device Performance |
---|---|---|
Audible Signal Timing | 100% timing agreement with a standard chronograph for alerting the patient to enter a score. | Tested using a schedule where the device alerted every 15 minutes. The Actiwatch-Score® audible alarm was in 100% timing agreement with the chronograph standard. (Pass) |
Patient Score Recording Accuracy | No errors or disagreement between entered scores and recorded scores. | Tested by programming the device to beep hourly from 12:00 noon to 21:00. A score was entered for each beep. Data was downloaded, and recorded scores were compared to entered scores. No errors nor disagreement were noted between the entered scores and the recorded scores. (Pass) |
2. Sample Size Used for the Test Set and Data Provenance:
- Sample Size:
- Audible Signal Timing: "a device" (singular) was used.
- Patient Score Recording Accuracy: "An Actiwatch-score" (singular) was used.
- Data Provenance: The studies appear to be prospective internal validation tests conducted by the manufacturer, Mini-Mitter Co., Inc. The country of origin is implicitly the USA, where Mini-Mitter Co., Inc. is located.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications:
- No external experts are mentioned for establishing ground truth for these specific tests.
- For the audible signal timing test, the ground truth was established by a chronograph standard.
- For the patient score recording accuracy test, the ground truth was the manually entered scores by a tester.
4. Adjudication Method for the Test Set:
- None explicitly stated or implied. The tests relied on direct comparison to a timing standard (chronograph) or the known input of a score.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done:
- No, an MRMC comparative effectiveness study was not done. The document focuses on the technical functionality of the device's new scoring feature, not on human-in-the-loop performance or comparison with human readers.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) was Done:
- Yes, the described tests are essentially standalone performance evaluations of the device's ability to accurately time its alerts and record user input. There is no human interpretation of data involved in the evaluation of these specific functionalities.
7. The Type of Ground Truth Used:
- Audible Signal Timing: Mechanical/digital standard (chronograph).
- Patient Score Recording Accuracy: Known user input/entered data.
8. The Sample Size for the Training Set:
- The document does not mention any training set or machine learning components for the described functionalities. The device's core function of sensing motion is based on an accelerometer, and the new score feature involves timing and data storage, which are deterministic operations.
9. How the Ground Truth for the Training Set Was Established:
- Since no training set is mentioned, this information is not applicable.
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(166 days)
ACTIWATCH
The Actiwatch® is an ultra-compact, lightweight, wrist-worn activity and ambient light monitor that can be used to analyze circadian rhythms, automatically collect and score data for sleep parameters, and assess activity in any instance where quantifiable analysis of physical motion is desirable.
The Actiwatch® is a compact, wrist-worn, battery-operated activity monitor whose physical characteristics are similar to a small wristwatch. The monitor consists of the activity monitor itself and a disposable wrist band. The Actiwatch® is intended for the measurement, storage, and analysis of body activity. The Actiwatch® can be attached to the subject's limb and through the use of an accelerometer, motion of that limb is measured, the activity stored within the activity monitor. A computer program is used to set un the Actiwatch® to collect data. This program is called Sleepwatch and runs on an IBM-compatible personal computer (PC). The major functions of Sleepwatch are to program the device to collect data, retrieve the data from the activity monitor, display the data, and to store the data for future reference and comparison. The Actiwatch® Reader is a compact interface device that provides a communications link between the Actiwatch® and the PC. The Actiwatch® Reader is connected to the serial communications port of the PC via a standard 9-conductor RS-232 cable. The Actiwatch® utilizes a motion sensor known as an "accelerometer" to monitor the occurrence and degree of motion. This type of sensor integrates the amplitude and speed of motion and produces a small signal whose magnitude and duration depend on the amount of motion. The activity signals are amplified and digitized by the on-board circuit. This information is stored in memory on board the device as activity counts.
The Mini-Mitter Co., Inc. Actiwatch® 510(k) submission [K983533] describes a device developed for measuring, storing, and analyzing body activity. The primary study presented focuses on the device's sensitivity to motion and inter-device variation rather than a clinical effectiveness study with human subjects.
Here's a breakdown of the requested information based on the provided text:
1. Table of Acceptance Criteria and Reported Device Performance
The document does not explicitly state formal "acceptance criteria" for performance that would typically be seen in more recent FDA submissions (e.g., minimum sensitivity, specificity, or accuracy percentages). Instead, it describes performance characteristics that were measured and compared to the predicate device.
Performance Characteristic | Acceptance Criteria (Implicit) | Reported Device Performance |
---|---|---|
Motion Sensitivity | Detect motion in the range of 0.01g and upwards (similar to predicate device). | Motion as low as 0.01g and as large as 10g can be measured. |
Inter-device Variation | Small differences between activity counts across devices, especially in typical human motion range (1G). | Smallest variation between devices in the 1G movement acceleration range (typical for human subjects). |
2. Sample Size Used for the Test Set and Data Provenance
- Sample Size for Test Set:
- Motion Sensitivity: Not explicitly stated as a number of devices or repetitions. The test involved "programming the device to collect data on one-minute intervals" and then subjecting "the device" to uniform simple harmonic motion. It appears to be a single device test or representative test of the device model's capability. Attachment No. 1 would likely provide more details, but it is not included in the provided text.
- Inter-device Variation: A sample of five devices was used.
- Data Provenance: The tests described appear to be conducted in a laboratory setting by the manufacturer, Mini-Mitter Co., Inc., for the purpose of demonstrating device performance. This would be considered retrospective in the context of the 510(k) submission, as the data was collected prior to market approval. The country of origin of the data is not explicitly stated but can be inferred as the USA, where the company is located.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications
This type of study did not involve human experts establishing ground truth. The assessments were technical performance measurements against known physical inputs:
- Motion Sensitivity: Ground truth was established by calculation from the physical setup – "From the rotational speed of the motor and the length of the lever arm, the maximum acceleration can be calculated." This is an objective, deterministic ground truth, not requiring human expert interpretation.
- Inter-device Variation: Ground truth was the controlled, known input motion applied to the devices, and the "ground truth" for comparison was the consistency of the readings among the devices.
4. Adjudication Method for the Test Set
Not applicable, as no human expert adjudication was involved in establishing the ground truth for these technical performance tests.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done
No, an MRMC comparative effectiveness study was not done. The submission focuses on the standalone performance characteristics of the device and its substantial equivalence to a predicate device, not on comparing human reader performance with and without AI assistance.
6. If a Standalone (i.e., Algorithm Only Without Human-in-the-Loop Performance) Was Done
Yes, the studies described are standalone performance assessments of the Actiwatch® device.
- The "Counts vs. motion" test assesses the device's ability to accurately measure motion (algorithm and hardware combined) against a physically controlled input.
- The "Variation between devices" test assesses the consistency of the device's measurements across different units.
Both are focused purely on the device's inherent performance.
7. The Type of Ground Truth Used
- Motion Sensitivity: Objective, physically calculated maximum acceleration based on a controlled mechanical setup (simple harmonic motion).
- Inter-device Variation: Controlled, known input motion (implicitly, the same motion applied to all five devices). The "ground truth" here is the expectation of consistent readings for a given input.
8. The Sample Size for the Training Set
The document does not describe the use of a "training set" in the context of machine learning, as this device (from 1999) predates widespread use of AI/ML in medical devices requiring such sets. The Actiwatch® utilizes an accelerometer and on-board circuitry to amplify and digitize signals, storing them as "activity counts." This is a deterministic signal processing approach, not a learned algorithm.
9. How the Ground Truth for the Training Set Was Established
Not applicable, as no training set for a machine learning algorithm was used.
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