(315 days)
SMART-D is a system for motion analysis, intended for the recording and analysis of human movement patterns in the fields of rehabilitation, sports medicine, ergonomics.
SMART-D is a motion capture and analysis system. It is based on optoelectronic technology and uses passive reflective markers, infrared cameras and strobes.
SMART-D executes the three-dimensional reconstruction of trajectories of a certain number of small reflective markers on the body to be analyzed.
Using a set of cameras placed all around the volume where the action is performed, the system acquires the movement of the subject; cameras position is computed after a calibration step.
Here's a breakdown of the acceptance criteria and the study information based on the provided document:
1. Table of Acceptance Criteria and Reported Device Performance
The provided document does not explicitly state quantitative (numerical) acceptance criteria for device performance such as accuracy, precision, or sensitivity/specificity. Instead, the acceptance criteria are described qualitatively as meeting "appropriate device specification or expected operation results" and performing "as the predicate devices."
The reported device performance is also presented qualitatively, focusing on the system's functionalities being equivalent to the predicate devices.
| Acceptance Criteria (Qualitative) | Reported Device Performance and Compliance |
|---|---|
| Meets appropriate device specification or expected operation results | All acceptance criteria were met in testing. |
| Is as effective and performs as the predicate devices | The SMART-D System is as effective and performs as the predicate devices. |
| Compliance with Electrical Safety Standards (AAMI/ANSI ES60601-1:2005) | The SMART-D System complies with AAMI/ANSI ES60601-1:2005 and amendments. |
| Compliance with EMC Standards (IEC 60601-1-2) | The SMART-D System complies with IEC 60601-1-2. |
| Functional equivalence to predicate devices for: | |
| * Calibration and Signals acquisition | SMARTcapture: Real-time visualization of signals of all integrated devices. (Equivalent to predicate functionalities) |
| * Trajectory reconstruction, signal elaboration | SMARTtracker: 3D kinematics reconstruction, validated by international scientific community protocols. (Equivalent to predicate functionalities) |
| * Management of acquired data, customizable analysis protocols | SMARTanalyzer: Tool for easy construction of analysis protocols. (Equivalent to predicate functionalities) |
| * Report drafting, data visualization | SMARTclinic: Multimedia customizable and web reporting. (Equivalent to predicate functionalities) |
2. Sample Size Used for the Test Set and Data Provenance
- Sample Size for Test Set: The document does not specify a numerical sample size for the test set used in performance evaluations. It refers to "non-clinical tests performed on the SMART-D System" and concludes that "all performance requirements defined by the System Requirement Specifications" were met.
- Data Provenance: The document does not explicitly state the country of origin of the data or whether the study was retrospective or prospective. Given that it's a 510(k) submission for a device manufactured in Italy (BTS SPA, Via della Croce Rossa 11, PD Italy 35129), it's plausible that testing occurred in Italy or internationally. The term "non-clinical tests" implies bench testing and verification, rather than clinical trials with patient data.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications
- The document does not mention the use of experts to establish a "ground truth" for a test set in the traditional sense (e.g., radiologists interpreting images). The device is a motion capture system, and the ground truth would likely refer to the accuracy of its measurements against known physical standards or highly precise reference systems.
- The document states that "3D kinematics reconstruction" is "Validated by international scientific community protocols." This suggests that the accuracy of the reconstruction is evaluated against established scientific methods rather than expert consensus on a specific dataset.
4. Adjudication Method for the Test Set
- No adjudication method (e.g., 2+1, 3+1) is mentioned, as the study does not involve human interpretation or subjective assessments that would require such a process. The performance evaluation is based on objective technical specifications and comparisons to predicate devices.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done
- No MRMC comparative effectiveness study was done. The device is a motion capture system, not an imaging diagnostic tool that would typically involve human readers interpreting cases.
6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done
- Yes, the performance data presented appears to be a standalone evaluation of the device. The "non-clinical tests" and the verification of functionalities (SMARTcapture, SMARTtracker, SMARTanalyzer, SMARTclinic) demonstrate the system's performance independent of human intervention in the motion capture and analysis process itself. The system is designed to objectively record and analyze movement.
7. The Type of Ground Truth Used
- The document implies that the ground truth for performance validation is based on "international scientific community protocols" for 3D kinematics reconstruction. This typically involves comparing the device's measurements against:
- Known physical standards: e.g., the movement of objects with precisely known dimensions or trajectories.
- Highly accurate reference systems: comparing the SMART-D's output to that of a more established or higher-precision motion capture system.
- Mathematical/Physical models: ensuring the reconstructed movements align with validated biomechanical principles.
No specific mention of pathology or outcomes data as ground truth is made.
8. The Sample Size for the Training Set
- The document does not mention a "training set" or "sample size for the training set." This is consistent with the nature of the device as a motion capture system. Such systems are typically calibrated using known physical configurations and their performance is then validated, rather than being "trained" on a dataset in the way a machine learning algorithm would be.
9. How the Ground Truth for the Training Set Was Established
- Not applicable, as no training set is mentioned for this type of device and evaluation. The system likely uses internal calibration routines and established mathematical models for its operation rather than a machine learning training paradigm.
§ 890.5360 Measuring exercise equipment.
(a)
Identification. Measuring exercise equipment consist of manual devices intended for medical purposes, such as to redevelop muscles or restore motion to joints or for use as an adjunct treatment for obesity. These devices also include instrumentation, such as the pulse rate monitor, that provide information used for physical evaluation and physical planning purposes., Examples include a therapeutic exercise bicycle with measuring instrumentation, a manually propelled treadmill with measuring instrumentation, and a rowing machine with measuring instrumentation.(b)
Classification. Class II (special controls). The device, when it is a measuring exerciser or an interactive rehabilitation exercise device for prescription use only, is exempt from the premarket notification procedures in subpart E of part 807 of this chapter subject to the limitations in § 890.9.