The time interval between consecutive heartbeats (interpulse interval, IPI) has previously been suggested for securing mobile-health solutions. This time interval is known to contain a degree of randomness, permitting the generation of a time- and person-specific identifier. It is commonly assumed that only devices trusted by a person can make physical contact with him/her, and that this physical contact allows each device to generate a similar identifier based on its own cardiac recordings. Under these conditions, the identifiers generated by different trusted devices can facilitate secure authentication. Recently, a wide range of techniques have been proposed for measuring heartbeats remotely, a prominent example of which is remote photoplethysmography (rPPG). These techniques may pose a significant threat to heartbeat-based security, as an adversary may pretend to be a trusted device by generating a similar identifier without physical contact, thus bypassing one of the core security conditions. In this paper, we assess the feasibility of such remote attacks using state-of-the-art rPPG methods. Our evaluation shows that rPPG has similar accuracy as contact PPG and, thus, forms a substantial threat to heartbeat-based-security systems that permit trusted devices to obtain their identifiers from contact PPG recordings. Conversely, rPPG cannot obtain an accurate representation of an identifier generated from electrical cardiac signals, making the latter invulnerable to state-of-the-art remote attacks.

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In heart-beat-based security, a security key is derived from the time difference between consecutive heart beats (the inter-pulse interval, IPI), which may, subsequently, be used to enable secure communication. While heart-beat-based security holds promise in mobile health (mHealth) applications, there currently exists no work that provides a detailed characterization of the delivered security in a real system. In this paper, we evaluate the strength of IPI-based security keys in the context of entity authentication. We investigate several aspects that should be considered in practice, including subjects with reduced heart-rate variability (HRV), different sensor-sampling frequencies, intersensor variability (i.e., how accurate each entity may measure heart beats) as well as average and worst-case-authentication time. Contrary to the current state of the art, our evaluation demonstrates that authentication using multiple, less-entropic keys may actually increase the key strength by reducing the effects of intersensor variability. Moreover, we find that the maximal key strength of a 60-bit key varies between 29.2 bits and only 5.7 bits, depending on the subject's HRV. To improve security, we introduce the inter-multi-pulse interval (ImPI), a novel method of extracting entropy from the heart by considering the time difference between nonconsecutive heart beats. Given the same authentication time, using the ImPI for key generation increases key strength by up to 3.4× (+19.2 bits) for subjects with limited HRV, at the cost of an extended key-generation time of 4.8× (+45 s).

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A promising alternative for treating absence seizures has emerged through closed-loop neurostimulation, which utilizes a wearable or implantable device to detect and subsequently suppress epileptic seizures. Such devices should detect seizures fast and with high accuracy, while respecting the strict energy budget on which they operate. Previous work has overlooked one or more of these requirements, resulting in solutions which are not suitable for continuous closed-loop stimulation. In this paper, we perform an in-depth design space exploration of a novel seizure-detection algorithm, which uses a complex Morlet wavelet filter and a static thresholding mechanism to detect absence seizures. We consider both the accuracy and speed of our detection algorithm, as well as various trade-offs with device autonomy when executed on a low-power processor. For example, we demonstrate that a minimal decrease in average detection rate of only 1.83% (from 92.72% to 90.89%) allows for a substantial increase in device autonomy (of 3.7x) while also facilitating faster detection (from 710 ms to 540 ms).@en

The cardiac interpulse interval (IPI) has recently been proposed tofacilitate key exchange for implantable medical devices (IMDs) using apatient's own heartbeats as a source of trust. While this form of key exchangeholds promise for IMD security, its feasibility is not fully understood due tothe simplified approaches found in related works. For example, previouslyproposed protocols have been designed without considering the limitedrandomness available per IPI, or have overlooked aspects pertinent to arealistic system, such as imperfect heartbeat detection or the energy overheadsimposed on an IMD. In this paper, we propose a new IPI-based key-exchangeprotocol and evaluate its use during medical emergencies. Our protocol employsfuzzy commitment to tolerate the expected disparity between IPIs obtained by anexternal reader and an IMD, as well as a novel way of tackling heartbeatmisdetection through IPI classification. Using our protocol, the expected timefor securely exchanging an 80-bit key with high probability (1-10−6) is roughlyone minute, while consuming only 88 μJ from an IMD.@en

Experimental devices aiming at real-time detection and suppression of epileptic-seizure events in live subjects already exist. However, to guarantee high detection accuracy, existing approaches employ high-accuracy detection filters that overlook the incurred energy costs, thus leading to unrealistic solutions for low-power implementations. In this short paper, we capitalize on the approximate nature of the seizure-detection phenomenon and propose an energy-efficient scheme for embedded, seizure-detection devices with trivial impact on detection accuracy. For a 1% reduction in filter detection accuracy we achieve a 3.7x increase in device-battery lifetime.@en

The Inter-Pulse-Interval (IPI) of heart beats has previously been suggested for security in mobile health (mHealth) applications. In IPI-based security, secure communication is facilitated through a security key derived from the time difference between heart beats. However, there currently exists no work which considers the effect on security of imperfect heart-beat (peak) detection. This is a crucial aspect of IPI-based security and likely to happen in a real system. In this paper, we evaluate the effects of peak misdetection on the security performance of IPI-based security. It is shown that even with a high peak detection rate between 99.9% and 99.0%, a significant drop in security performance may be observed (between -70% and -303%) compared to having perfect peak detection. We show that authenticating using smaller keys yields both stronger keys as well as potentially faster authentication in case of imperfect heart beat detection. Finally, we present an algorithm which tolerates the effect of a single misdetected peak and increases the security performance by up to 155%.

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Recent work on wireless Implantable Medical Devices (IMDs) has revealed the need for secure communication in order to prevent data theft and implant abuse by malicious attackers. However, security should not be provided at the cost of patient safety and an IMD should, thus, remain accessible during an emergency regardless of device security. In this paper, we present a novel method of providing IMD emergency access, based on generating Entity Identifiers (EI) using the Inter-Pulse Intervals (IPIs) of heartbeats. We evaluate the current state-of-the-art in EI-generation in terms of security and accessibility for healthy subjects with a wide range of heart rates. Subsequently, we present an adaptive EI-generation algorithm which takes the heart rate into account, maintaining an acceptable emergency-mode activation time (between 5-55.4 s) while improving security by up to 3.4x for high heart rates. Finally, we show that activating emergency mode may consume as little as 0.24μJ from the IMD battery.

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In this paper, we describe the design and implementation of a new fault-tolerant RISC-processor architecture suitable for a design framework targeting biomedical implants. The design targets both soft and hard faults and is original in efficiently combining as well as enhancing classic fault-tolerance techniques. The proposed architecture allows run-time tradeoffs between performance and fault tolerance by means of instruction-level configurability. The system design is synthesized for UMC 90nm CMOS standard-process and is evaluated in terms of fault coverage, area, average power consumption, total energy consumption and performance for various duplication policies and test-sequence schedules. It is shown that area and power overheads of approximately 25% and 32%, respectively, are required to implement our techniques on the baseline processor. The major overheads of the proposed architecture are performance (up to 107%) and energy consumption (up to 157%). It is observed that the average power consumption is often reduced when a higher degree of fault tolerance is targeted. It is shown that test sequences can effectively be scheduled during the available program stalls and that nearly all soft faults are tolerated by using instruction duplication. The main advantages of the proposed architecture are the high portability of the introduced architecture-level fault-tolerance techniques, the flexibility in trading processor overheads for required fault-tolerance degree as well as affordable area and power consumption overheads.

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