Effect of direct voltage induction by low-frequency security systems on neurostimulator lead.

Low-frequency (LF) security systems, such as antitheft electronic article surveillance (EAS) gates emit strong magnetic fields that could potentially interfere with neurostimulator operation. Some patients reported pain and shocking sensations near EAS gates, even after they turned off their pulse generator. To investigate the direct voltage induction of EAS systems on neurostimulator leads, we evaluated voltages induced by two EAS systems (14 kHz continuous wave or 58 kHz pulsed) on a 40 cm sacral neurostimulator lead formed in a circular loop attached to a pulse generator that was turned off. The lead and neurostimulator were mounted in a saline-filled rectangular phantom placed within electromagnetic fields emitted by EAS systems. The measured voltage waveforms were applied to computational models of spinal nerve axons to predict whether these voltages may evoke action potentials. Additional in vitro testing was performed on the semicircular lead geometry, to study the effect of lead geometry on EAS induced voltages. While standard neurostimulator testing per ISO 14708-3:2017 recommends electromagnetic compatibility testing with LF magnetic fields for induction of malfunctions of the active electronic circuitry while generating intended stimulating pulses, our results show that close to the EAS antenna frames, the induced voltage on the lead could be strong enough to evoke action potentials, even with the pulse generator turned off. This work suggests that patient reports of pain and shocking sensations when near EAS systems could also be correlated with the direct EAS-induced voltage on neurostimulator lead.

Static magnetic field measurements of smart phones and watches and applicability to triggering magnet modes in implantable pacemakers and implantable cardioverter-defibrillators.

BACKGROUND: Implantable pacemakers and implantable cardioverter-defibrillators (ICDs) are designed to include a "magnet mode" feature that can be activated from magnets stronger than 10 G. This feature is designed to be used when a patient is undergoing a procedure where electromagnetic interference is possible, or anytime suspension of tachycardia detection and therapy is needed. A publication in Heart Rhythm demonstrates an iPhone 12 triggering the magnet mode of a Medtronic ICD. OBJECTIVE: The purpose of this study is to determine the separation distance between consumer electronic devices that may create magnetic interference, including cell phones and smart watches, and implantable pacemakers and ICDs where magnet mode can be triggered. METHODS: The static magnetic fields of the iPhone 12 models and Apple Watch were measured at several planes in 1 cm resolution using an FW Bell 5180 Gauss Meter with STD18-0404 Transverse probe (unidirectional probe). RESULTS: All iPhone 12 and Apple Watch 6 models tested have static magnetic fields significantly greater than 10 G in close proximity (1-11 mm), which attenuates to below 10 G between 11 and 20 mm. CONCLUSION: The findings of this study support the US Food and Drug Administration recommendation that patients keep any consumer electronic devices that may create magnetic interference, including cell phones and smart watches, at least 6 inches away from implanted medical devices, in particular pacemakers and cardiac defibrillators.

Determining EMC Test Levels for Implantable Devices in Bipolar Lead Configuration.

Certain low-frequency magnetic fields cause interference in implantable medical devices. Electromagnetic compatibility (EMC) standards prescribe injecting voltages into a device under evaluation to simplify testing while approximating or simulating real-world exposure situations to low-frequency magnetic fields. The EMC standard ISO 14117:2012, which covers implantable pacemakers and implantable cardioverter defibrillators (ICDs), specifies test levels for the bipolar configuration of sensing leads as being one-tenth of the levels for the unipolar configuration. The committee authoring this standard questioned this testing level difference and its clinical relevance. To evaluate this issue of EMC test levels, we performed both analytical calculations and computational modeling to determine a basis for this difference. Analytical calculations based upon Faraday's law determined the magnetically induced voltage in a 37.6-cm lead. Induced voltages were studied in a bipolar lead configuration with various spacing between a distal tip electrode and a ring electrode. Voltages induced in this bipolar lead configuration were compared with voltages induced in a unipolar lead configuration. Computational modeling of various lead configurations was performed using electromagnetic field simulation software. The two leads that were insulated, except for the distal and proximal tips, were immersed in a saline-conducting media. The leads were parallel and closely spaced to each other along their length. Both analytical calculations and computational modeling support continued use of a one-tenth amplitude reduction for testing pacemakers and ICDs in bipolar mode. The most recent edition of ISO 14117 includes rationale from this study.

5 GHz Band LTE-LAA Signal Selection for Use as the Unintended Signal in ANSI C63.27 Wireless Coexistence Testing.

This article details the experimental work conducted at the Electromagnetic Compatibility and Wireless Laboratory, U.S. Food and Drug Administration, to investigate the use of LAA signals for wireless coexistence testing. A software defined radio platform was deployed to generate realistic LAA signals and measure the wireless coexistence impact on the LAA communication link. The equipment under test (EUT) used IEEE 802.11ac as an example incumbent technology in the 5 GHz band. The standardized radiated anechoic chamber method was used for testing. Results highlight the mutual coexistence impact of LAA in the 5 GHz band and suggest that selecting an LAA signal with the maximum possible channel time occupancy and the highest possible modulation and coding scheme (MCS) yields the most impactful coexistence situation on both the EUT and the LAA system. Additionally, an analysis of the internal LAA system states during coexistence testing is presented to document the inverse relationship between LAA transmit and wait times during coexistence and the adverse impact of challenging coexistence scenarios on successful channel access. Finally, the risk management process of wireless coexistence for medical devices is summarized and associated with coexistence testing.

A Case Study of Medical Device Wireless Coexistence Evaluation.

This article aims to provide a narrative for addressing wireless coexistence in medical devices to help medical device developers, test engineers, and regulatory affairs personnel throughout the device life cycle. Accordingly, we present a case-study covering the coexistence evaluation process including the risk analysis of the wireless functionality of a hypothetical medical device, determining the corresponding risk category, specification of the device functional wireless performance (FWP), wireless coexistence testing, and measurement of the intended/untended signal ratio. Also, we propose a simple method for translating the test outcome into user recommendations for minimum/maximum separation distances between the device, its intended companion, and the source of unintended signals.

PESA: Probabilistic Efficient Storage Algorithm for Time-Domain Spectrum Measurements.

Wireless communication is an essential part of daily life for users globally with applications in medical devices, cellular phones, Internet of Things nodes, and others. Accordingly, there is a need to understand the patterns and properties of radio frequency spectrum use by acquiring accurate spectrum utilization measurements. However, the massive storage volume needed to execute spectrum surveys-especially when a fast sampling rate is used-is an impeding factor in terms of cost and ease-of-access. In this article, a probabilistic efficient storage algorithm (PESA) is proposed to facilitate high-accuracy, time-domain spectrum surveys conducted at a fast sample acquisition rate to detect sporadic spectrum occupancy patterns that could be on the order of microseconds. PESA divides the dynamic range of a monitoring equipment into bins-each represented by one component of a Gaussian mixture model (GMM). Windows of activity and inactivity in the measurements are established by comparing with a threshold and then indicators to the GMM component that best describes a window are recorded. Hence, reducing required storage volume. Results demonstrate that ≈ 99% reduction in storage volume is achievable while maintaining an accurate estimation of channel utilization and activity/inactivity periods. Furthermore, a Lab-VIEW implementation of PESA on a hardware platform was executed and used to survey Wi-Fi channel 1 in a healthcare environment for seven consecutive hours. Although more than 25 billion samples were observed, resulting data only occupied 96.28 megabytes.

Wireless Coexistence Testing in the 5 GHz Band with LTE-LAA Signals.

Exploiting unlicensed spectrum bands for cellular communication is a rapidly embraced trend by industry stakeholders. Accordingly, the specifications of Long Term Evolution (LTE) were extended in Release 13 to allow unlicensed spectrum operation, also known as LTE-Licensed Assisted Access (LAA). LTE is widely adopted, and there is a potential for significant coexistence impact of LTE-LAA on users of unlicensed spectrum including wireless medical devices, whether adopters of the new technology or incumbents. Therefore, work was initiated to revise and update the American National Standards Institute (ANSI) C63.27 standard for evaluation of wireless coexistence. This paper details the experimental work conducted at the Electromagnetic Compatibility and Wireless Laboratory, U.S. Food and Drug Administration, to investigate the use of LAA signals for wireless coexistence testing. A software defined radio platform was deployed to generate realistic LAA signals and measure the wireless coexistence impact on the LAA communication link. The equipment under test (EUT) used IEEE 802.11ac as an example incumbent technology in the 5 GHz band. The standardized radiated anechoic chamber method was used for testing. Results highlight the mutual coexistence impact of LAA in the 5 GHz band and suggest that selecting an LAA signal with the maximum possible channel time occupancy and the highest possible modulation and coding scheme (MCS) yields the most impactful coexistence situation on both the EUT and the LAA system.

An outlook on wireless coexistence with focus on medical devices.

The use of shared and unlicensed radio spectrum has been the impetus of innovative and widely used technologies (e.g., Wi-Fi, Bluetooth, and others)-driving the scene of ubiquitous connectivity for devices, sensors, and peripherals in an encompassing Internet of Things (IoT). However, coexisting technologies operating in unlicensed bands need to share limited spectrum resources while attempting to offer desired performance. This could prove challenging as channel access is not guaranteed, which raises concerns for wireless coexistence in sensitive applications like medical devices. In this article, we provide a brief review of topics forming the current stage of wireless coexistence in research, industry, and regulatory circles. We present the standardization activities for the evaluation of wireless coexistence, and recent advancements of unlicensed spectrum technologies such as Wi-Fi, Bluetooth, and Long Term Evolution (LTE) in unlicensed bands, along with proposed evaluation methods.

On the Coexistence of LTE-LAA in the Unlicensed Band: Modeling and Performance Analysis.

Long term evolution (LTE) technology leveraging the unlicensed band is anticipated to provide a solution for the challenges stemming from the rapid growth of mobile wireless services, the scarcity of available licensed spectrum, and the expected significant increase in mobile data traffic. Ensuring fair operation in terms of spectrum sharing with current unlicensed spectrum incumbents is a key concern relative to the success and viability of Unlicensed LTE (U-LTE). This paper addresses the problem of modeling and evaluating the coexistence of LTE license-assisted-access in the unlicensed band. The paper presents a novel analytical model using Markov chain to accurately model the LAA listen-before-talk scheme, as specified in the final technical specification 36.213 of 3GPP release 13 and 14. Furthermore, model validation is demonstrated through numerical and simulation results comparison. Model performance evaluation is examined and contrasted with IEEE 802.11 distributed coordination function. Finally, a comprehensive coexistence performance analysis is conducted for both homogeneous and heterogeneous network scenarios and coexistence results are presented and discussed herein.

Estimating the Likelihood of Wireless Coexistence Using Logistic Regression: Emphasis on Medical Devices.

Medical device manufacturers incorporate wireless technology in their designs to offer convenience and agility to both patients and caregivers. However, the use of unlicensed radio spectrum bands by both medical devices and other equipment raises concerns about wireless coexistence. Work by the accredited standards committee C63 of the American National Standards Institute (ANSI) to provide the community with a consensus standard for coexistence evaluation resulted in the publication of the ANSI C63.27 standard, which was later recognized by the U.S. Food and Drug Administration. Estimating the likelihood of wireless coexistence of a system under test (SUT) in a given environment is central to the evaluation and reporting of wireless coexistence, as made clear in the C63.27 standard. However, no method to perform this estimation is provided. In this paper, we propose the use of logistic regression (LR) to estimate the likelihood of wireless coexistence of a medical device in its intended environment. Radiated open environment coexistence testing was used to realize a test scenario in which the interfering network was IEEE 802.11n Wi-Fi and the SUT was ZigBee; exemplary wireless technologies for interfering network and medical device, respectively. LR model fitting was then performed to derive a model that describes the performance of SUT under a range of wireless coexistence phenomena. Finally, results were incorporated with the outcome of a spectrum survey using Monte Carlo simulation to estimate the SUT likelihood of wireless coexistence in a hospital environment.

Practical aspects of wireless medical device coexistence testing.

Integrating wireless technology in medical devices has proved beneficial for both patients and caregivers. However, the use of shared, unlicensed spectrum bands by both medical and non-medical wireless devices has raised concerns about wireless coexistence. The challenge of incorporating wireless communication into a medical device is to ensure reasonable medical device effectiveness and patient safety. Consequently, work to develop a standardized process to assess wireless coexistence, primarily for wireless medical devices, was carried by Subcommittee 7 of American National Standards Institute (ANSI)-accredited standards committee (ASC) C63 and the Wireless Working Group (SM-WG06) of the Association for the Advancement of Medical Instrumentation (AAMI). Both groups have recently released their respective documents. In this article, we discuss practical aspects of wireless coexistence testing-in the realm of ANSI C63.27 and AAMI TIR69-to help answer basic, yet important, questions such as what to test, how to test, and how to present results.

Characterizing the 2.4 GHz Spectrum in a Hospital Environment: Modeling and Applicability to Coexistence Testing of Medical Devices.

The increasing use of shared, unlicensed spectrum bands by medical devices and nonmedical products highlights the need to address wireless coexistence to ensure medical device safety and effectiveness. This paper provides the first step to approximate the probability of a device coexisting in its intended environment by providing a generalized framework for modeling the environment. The application of this framework is shown through an 84-day spectrum survey of the 2.4-2.48 GHz industrial, scientific, and medical band in a hospital environment in the United States. A custom platform was used to monitor power flux spectral density and record received power. Channel utilization of three nonoverlapping channels of 20 MHz bandwidth-relative to IEEE 802.11 channels 1, 6, and 11-were calculated and fitted to a generalized extreme value distribution. Low channel utilization was observed (<10%) in the surveyed environment with sporadic occurrences of higher channel utilization (>50%). Reported findings can be complementary to wireless coexistence testing. This paper can provide input to the development of a consensus standard for wireless device coexistence test methods and a consensus document focused on wireless medical device coexistence risk management.

Feasibility results of an electromagnetic compatibility test protocol to evaluate medical devices to radio frequency identification exposure.

BACKGROUND: The use of radio frequency identification (RFID) systems in healthcare is increasing, and concerns for electromagnetic compatibility (EMC) pose one of the biggest obstacles for widespread adoption. Numerous studies have demonstrated that RFID systems can interfere with medical devices; however, the majority of past studies relied on time-consuming and burdensome test schemes based on ad hoc test methods applied to individual RFID systems. METHODS: This paper presents the results of using an RFID simulator that allows for faster evaluation of RFID-medical device EMC against a library of RFID test signals at various field strengths. RESULTS: The results of these tests demonstrate the feasibility and adequacy of simulator testing and can be used to support its incorporation into applicable consensus standards. CONCLUSIONS: This work can aid the medical device community in better assessing the risks associated with medical device exposure to RFID.

Adhoc electromagnetic compatibility testing of non-implantable medical devices and radio frequency identification.

BACKGROUND: The use of radiofrequency identification (RFID) in healthcare is increasing and concerns for electromagnetic compatibility (EMC) pose one of the biggest obstacles for widespread adoption. Numerous studies have documented that RFID can interfere with medical devices. The majority of past studies have concentrated on implantable medical devices such as implantable pacemakers and implantable cardioverter defibrillators (ICDs). This study examined EMC between RFID systems and non-implantable medical devices. METHODS: Medical devices were exposed to 19 different RFID readers and one RFID active tag. The RFID systems used covered 5 different frequency bands: 125-134 kHz (low frequency (LF)); 13.56 MHz (high frequency (HF)); 433 MHz; 915 MHz (ultra high frequency (UHF])) and 2.4 GHz. We tested three syringe pumps, three infusion pumps, four automatic external defibrillators (AEDs), and one ventilator. The testing procedure is modified from American National Standards Institute (ANSI) C63.18, Recommended Practice for an On-Site, Ad Hoc Test Method for Estimating Radiated Electromagnetic Immunity of Medical Devices to Specific Radio-Frequency Transmitters. RESULTS: For syringe pumps, we observed electromagnetic interference (EMI) during 13 of 60 experiments (22%) at a maximum distance of 59 cm. For infusion pumps, we observed EMI during 10 of 60 experiments (17%) at a maximum distance of 136 cm. For AEDs, we observed EMI during 18 of 75 experiments (24%) at a maximum distance of 51 cm. The majority of the EMI observed was classified as probably clinically significant or left the device inoperable. No EMI was observed for all medical devices tested during exposure to 433 MHz (two readers, one active tag) or 2.4 GHz RFID (two readers). CONCLUSION: Testing confirms that RFID has the ability to interfere with critical medical equipment. Hospital staff should be aware of the potential for medical device EMI caused by RFID systems and should be encouraged to perform on-site RF immunity tests prior to RFID system deployment or prior to placing new medical devices in an RFID environment. The methods presented in this paper are time-consuming and burdensome and suggest the need for standard test methods for assessing the immunity of medical devices to RFID systems.

Wireless Coexistence and EMC of Bluetooth and 802.11b Devices in Controlled Laboratory Settings.

This paper presents experimental testing that has been performed on wireless communication devices as victims of electromagnetic interference (EMI). Wireless victims included universal serial bus (USB) network adapters and personal digital assistants (PDAs) equipped with IEEE 802.11b and Bluetooth technologies. The experimental data in this paper was gathered in an anechoic chamber and a gigahertz transverse electromagnetic (GTEM) cell to ensure reliable and repeatable results. This testing includes: Electromagnetic compatibility (EMC) testing performed in accordance with IEC 60601-1-2, an in-band sweep of EMC testing, and coexistence testing. The tests in this study show that a Bluetooth communication was able to coexist with other Bluetooth devices with no decrease in throughput and no communication breakdowns. However, testing revealed a significant decrease in throughput and increase in communication breakdowns when an 802.11b source is near an 802.11b victim. In a hospital setting decreased throughput and communication breakdowns can cause wireless medical devices to fail. It is therefore vital to have an understanding of the effect EMI can have on wireless communication devices.

Analysis of induced electrical currents from magnetic field coupling inside implantable neurostimulator leads.

BACKGROUND: Over the last decade, the number of neurostimulator systems implanted in patients has been rapidly growing. Nearly 50, 000 neurostimulators are implanted worldwide annually. The most common type of implantable neurostimulators is indicated for pain relief. At the same time, commercial use of other electromagnetic technologies is expanding, making electromagnetic interference (EMI) of neurostimulator function an issue of concern. Typically reported sources of neurostimulator EMI include security systems, metal detectors and wireless equipment. When near such sources, patients with implanted neurostimulators have reported adverse events such as shock, pain, and increased stimulation. In recent in vitro studies, radio frequency identification (RFID) technology has been shown to inhibit the stimulation pulse of an implantable neurostimulator system during low frequency exposure at close distances. This could potentially be due to induced electrical currents inside the implantable neurostimulator leads that are caused by magnetic field coupling from the low frequency identification system. METHODS: To systematically address the concerns posed by EMI, we developed a test platform to assess the interference from coupled magnetic fields on implantable neurostimulator systems. To measure interference, we recorded the output of one implantable neurostimulator, programmed for best therapy threshold settings, when in close proximity to an operating low frequency RFID emitter. The output contained electrical potentials from the neurostimulator system and those induced by EMI from the RFID emitter. We also recorded the output of the same neurostimulator system programmed for best therapy threshold settings without RFID interference. Using the Spatially Extended Nonlinear Node (SENN) model, we compared threshold factors of spinal cord fiber excitation for both recorded outputs. RESULTS: The electric current induced by low frequency RFID emitter was not significant to have a noticeable effect on electrical stimulation. CONCLUSIONS: We demonstrated a method for analyzing effects of coupled magnetic field interference on implantable neurostimulator system and its electrodes which could be used by device manufacturers during the design and testing phases of the development process.

Electromagnetic compatibility of implantable neurostimulators to RFID emitters.

BACKGROUND: The objective of this study is to investigate electromagnetic compatibility (EMC) of implantable neurostimulators with the emissions from radio frequency identification (RFID) emitters. METHODS: Six active implantable neurostimulators with lead systems were tested for susceptibility to electromagnetic fields generated by 22 RFID emitters. These medical devices have been approved for marketing in the U.S. for a number of intended uses that include: epilepsy, depression, incontinence, Parkinsonian tremor and pain relief. Each RFID emitter had one of the following carrier frequencies: 125 kHz, 134 kHz, 13.56 MHz, 433 MHz, 915 MHz and 2.45 GHz. RESULTS: The test results showed the output of one of the implantable neurostimulators was inhibited by 134 kHz RFID emitter at separation distances of 10 cm or less. The output of the same implantable neurostimulator was also inhibited by another 134 kHz RFID emitter at separation distances of 10 cm or less and also showed inconsistent pulsing rate at a separation distance of 15 cm. Both effects occurred during and lasted through out the duration of the exposure. CONCLUSIONS: The clinical significance of the effects was assessed by a clinician at the U.S. Food and Drug Administration. The effects were determined to be clinically significant only if they occurred for extended period of time. There were no observed effects from the other 5 implantable neurostimulators or during exposures from other RFID emitters.

Electromagnetic compatibility testing of implantable neurostimulators exposed to metal detectors.

This paper presents results of electromagnetic compatibility (EMC) testing of three implantable neurostimulators exposed to the magnetic fields emitted from several walk-through and hand-held metal detectors. The motivation behind this testing comes from numerous adverse event reports involving active implantable medical devices (AIMDs) and security systems that have been received by the Food and Drug Administration (FDA). EMC testing was performed using three neurostimulators exposed to the emissions from 12 walk-through metal detectors (WTMDs) and 32 hand-held metal detectors (HHMDs). Emission measurements were performed on all HHMDs and WTMDs and summary data is presented. Results from the EMC testing indicate possible electromagnetic interference (EMI) between one of the neurostimulators and one WTMD and indicate that EMI between the three neurostimulators and HHMDs is unlikely. The results suggest that worst case situations for EMC testing are hard to predict and testing all major medical device modes and setting parameters are necessary to understand and characterize the EMC of AIMDs.