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510(k) Data Aggregation
(179 days)
SmartTENS
This device is intended for the relief of pain associated with sore or aching muscles of the lower back, arms, or legs due to strain from exercise or normal household and work activities.
SmartTENS is a portable battery powered T.E.N.S. device with a wireless remote control feature for over-the-counter use, mainly operating in home, clinic, or hospital environments.
There are three control buttons on the unit itself: ON/OFF, intensity UP and intensity DOWM. The device is also designed to be controlled wirelessly through Bluetooth 4.0 connection (Frequency: 2402.0 - 2480.0 MHz) by a matched smart phone, which is featuring a mobile application (App) developed by EasyMed Instruments Co., Ltd.
A user entered 6-digit security code ensures the access to the device can only be the user's matched smart phone, thus avoiding unauthorized controls to the device.
There are totally seven (7) modes that are intended for pain relieving treatments to the following areas: Shoulder/ Arm, Lower Back and Leg/Foot. The specifications of each mode will be described in greater details in the User Manual.
Here's a breakdown of the acceptance criteria and study information based on the provided text, focusing on the SmartTENS device:
1. Table of Acceptance Criteria and Reported Device Performance
The document does not explicitly state "acceptance criteria" for the SmartTENS in the form of specific performance metrics (e.g., accuracy, sensitivity, specificity) expected from a clinical study. Instead, it details the technical specifications and performance characteristics of the SmartTENS and compares them to predicate devices, demonstrating substantial equivalence.
The reported device performance is implicitly shown through its compliance with various electrical and medical device safety standards and a usability study.
| Attribute/Criteria Type | Acceptance Criteria (Implied / Comparator) | Reported Device Performance (SmartTENS) |
|---|---|---|
| Indications for Use | Relief of pain associated with sore or aching muscles of the lower back, arms, or legs due to strain from exercise or normal household and work activities (Same as Predicate 1, similar to Predicate 2 but broader for SmartTENS). | Intended for the relief of pain associated with sore or aching muscles of the lower back, arms, or legs due to strain from exercise or normal household and work activities. |
| Product Code | NUH (Predicate 1), GZJ, NYN (Predicate 2) | NUH |
| Regulation No. | 21 CFR 882.5890 | 21 CFR 882.5890 |
| Wireless Control | No (Predicate 1), Yes (Predicate 2) | Yes (Bluetooth 4.0) |
| Number of Output Modes | 8 (Predicate 1), 4 (Predicate 2) | 7 |
| Number of Output Channels | 2 (Predicate 1), 1 (Predicate 2) | 1 |
| Waveform | Biphasic rectangular, Monophasic rectangular (Predicate 1), Pulsed biphasic rectangular (Predicate 2) | Biphasic rectangular, Monophasic rectangular |
| Maximum Output Voltage (500Ω) | 68V (Predicate 1), 35.2 V (Predicate 2) | 68V |
| Maximum Output Current (500Ω) | 133mA (Predicate 1), 70mA (Predicate 2) | 133mA |
| Maximum Phase Charge (500Ω) | 20.02µC (Predicate 1), 11.6µC (Predicate 2) | 20.02µC |
| Maximum Average Current (500Ω) | 3.0375mA (Predicate 1), 0.63mA (Predicate 2) | 3.0375mA |
| Maximum Current Density (500Ω) | 0.188mA/cm² (Predicate 1), 0.00149 mA/cm² (Predicate 2) | 0.066mA/cm² |
| Maximum Average Power Density (500Ω) | 7.52mW/cm² (Predicate 1), 0.0313mW/cm² (Predicate 2) | 2.66mW/cm² |
| Frequency (Hz) | From 1Hz to 150Hz (Predicate 1), From 5Hz to 120Hz (Predicate 2) | From 1Hz to 150Hz |
| Pulse Duration (µs) | 50-250µs (Predicate 1), 120-250µs (Predicate 2) | 50-250µs |
| Burst Mode | Yes (Predicate 1), No (Predicate 2) | Yes |
| Timer Range (min) | 20min, 25min, 30min, 40min (Predicate 1), 30min (Predicate 2) | 20min, 25min, 30min, 40min depending on preset program |
| Power Source | 2 Alkaline AA 1.5V (Predicate 1), 2 Alkaline AAA 1.5V DC + 1 CR2032 Lithium (Predicate 2) | 3.7V rechargeable lithium battery |
| Microprocessor Control | Yes | Yes |
| Automatic Overload Trip | Yes (Predicate 1), No (Predicate 2) | Yes |
| Automatic No-load Trip | Yes (Predicate 1), No (Predicate 2) | Yes |
| Automatic Shut-off | Yes | Yes |
| User Override Control | Yes | Yes |
| Indicator Display (On/Off, Low Battery, Voltage/Current Level, Output Mode, Time to cut-off) | Yes for all (Predicate 1), Yes for On/Off & Low Battery (Predicate 2) | Yes for all |
| Electrode Compliance with 21 CFR 898 | Yes | Yes |
| Usability | Users able to use device correctly and safely. | Usability study showed users were able to use the device correctly and safely. |
| Electrical Safety | Compliance with AAMI/ANSI ES60601-1:2005/(R)2012 | Complies with AAMI/ANSI ES60601-1:2005/(R)2012 |
| EMC | Compliance with AAMI/ANSI/IEC 60601-1-2:2007/(R)2012 and IEC 60601-1-11 | Complies with AAMI/ANSI/IEC 60601-1-2:2007/(R)2012 and IEC 60601-1-11 |
| Nerve & Muscle Stimulator Specific Safety | Compliance with IEC 60601-2-10 Edition 2.0 2012-06 | Complies with IEC 60601-2-10 Edition 2.0 2012-06 |
| Risk Management | Compliance with ISO 14971: Second Edition 2007-03-01 | Complies with ISO 14971: Second Edition 2007-03-01 |
| Usability Engineering | Compliance with IEC 60601-1-6 Edition 3.0 2010-01 | Complies with IEC 60601-1-6 Edition 3.0 2010-01 |
| Software Life Cycle Processes | Compliance with IEC 62304 First Edition 2006-05 | Complies with IEC 62304 First Edition 2006-05 |
2. Sample Size Used for the Test Set and Data Provenance
The document mentions that a "usability study was conducted," but it does not specify the sample size for this study or any other test set. The data provenance (country of origin, retrospective/prospective) for any test data is also not mentioned.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts
This information is not provided in the document. The usability study would likely have involved user feedback, but the "ground truth" for a medical device's performance often relates to objective measures of efficacy or safety, which are not detailed here in terms of expert evaluation.
4. Adjudication Method for the Test Set
This information is not provided.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
A MRMC comparative effectiveness study was not conducted for this device as it is a Transcutaneous Electrical Nerve Stimulator (T.E.N.S.) which directly delivers electrical current, rather than an imaging or diagnostic AI requiring human reader interpretation. The purpose of this submission is to demonstrate substantial equivalence to predicate devices based on technical specifications and safety standards, not a comparative effectiveness study involving human interpretation.
6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study
The SmartTENS is a physical medical device, not an algorithm in the context of AI. Therefore, a standalone (algorithm only) performance study as typically understood for AI/software devices was not performed or is not applicable. Its performance is assessed through its output characteristics and compliance with electrical and safety standards.
7. Type of Ground Truth Used
For the SmartTENS, the "ground truth" for its performance is established through:
- Compliance with recognized electrical and medical device safety standards (e.g., AAMI/ANSI ES60601-1, IEC 60601-1-2, IEC 60601-2-10, ISO 14971, IEC 60601-1-6, IEC 62304). This demonstrates that the device operates within established safe and effective parameters for TENS devices.
- Usability Feedback: The usability study inherently uses user experience (ease of use, safety observation) as a form of "ground truth" to determine if users can correctly and safely operate the device.
8. Sample Size for the Training Set
The SmartTENS is a hardware device with embedded software (for control and modes), but not an AI/machine learning model in the sense that would require a "training set" of data for learning and prediction. Therefore, a training set sample size is not applicable and not mentioned.
9. How the Ground Truth for the Training Set Was Established
As there is no "training set" for an AI/machine learning model, this question is not applicable. The "ground truth" for the device's design and functionality is based on established engineering principles, regulatory standards, and the performance characteristics of predicate devices.
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