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Robust Epileptic Seizure Detection on Wearable Systems with Reduced False-Alarm Rate

Epilepsy affects more than 50 million people and ranks among the most common neurological diseases worldwide. Despite advances in treatment, one-third of patients still suffer from refractory epilepsy. Wearable devices for real-time patient monitoring can potentially improve the quality of life for such patients and reduce the mortality rate due to seizure-related accidents and sudden death in epi

Butterfly attack : Adversarial manipulation of temporal properties of cyber-physical systems

Increasing internet connectivity poses an existential threat for cyber-physical systems. Securing these safety-critical systems becomes an important challenge. Cyber-physical systems often comprise several control applications that are implemented on shared platforms where both high and low criticality tasks execute together (to reduce cost). Such resource sharing may lead to complex timing behavi

Minimal Adversarial Perturbations in Mobile Health Applications : The Epileptic Brain Activity Case Study

Today, the security of wearable and mobile-health technologies represents one of the main challenges in the Internet of Things (IoT) era. Adversarial manipulation of sensitive health-related information, e.g., if such information is used for prescribing medicine, may have irreversible consequences involving patients' lives. In this article, we demonstrate the power of such adversarial attacks base

Self-aware machine learning for multimodal workload monitoring during manual labor on edge wearable sensors

Editor's notes: This article discusses self-awareness in wearable edge devices to enable real-time and long-term health monitoring. The authors use the notion of self-awareness to improve the battery life of edge wearable sensors for multimodal health and workload monitoring. This approach leads to a 27.6% lower energy consumption with less than 6% of performance loss. - Umit Y. Ogras, Arizona Sta

Multi-Modal Acute Stress Recognition Using Off-the-Shelf Wearable Devices

Monitoring stress and, in general, emotions has attracted a lot of attention over the past few decades. Stress monitoring has many applications, including high-risk missions and surgical procedures as well as mental/emotional health monitoring. In this paper, we evaluate the possibility of stress and emotion monitoring using off-the-shelf wearable sensors. To this aim, we propose a multi-modal mac

A Self-Learning Methodology for Epileptic Seizure Detection with Minimally-Supervised Edge Labeling

Epilepsy is one of the most common neurological disorders and affects over 65 million people worldwide. Despite the continuing advances in anti-epileptic treatments, one third of the epilepsy patients live with drug resistant seizures. Besides, the mortality rate among epileptic patients is 2 - 3 times higher than in the matching group of the general population. Wearable devices offer a promising

Self-aware wearable systems in epileptic seizure detection

Today, wearable systems are facing fundamental barriers in terms of battery lifetime and quality of their results. The main challenge in wearable systems is to increase the battery lifetime, while maintaining the machine-learning performance of the system. A recently proposed concept for overcoming this challenge is self-awareness, which increases system's knowledge of itself and the surrounding e

Resource-Aware Distributed Epilepsy Monitoring Using Self-Awareness From Edge to Cloud

The integration of wearable devices in humans' daily lives has grown significantly in recent years and still continues to affect different aspects of high-quality life. Thus, ensuring the reliability of the decisions becomes essential in biomedical applications, while representing a major challenge considering battery-powered wearable technologies. Transferring the complex and energy-consuming com

Security-aware routing and scheduling for control applications on ethernet TSN networks

Today, it is common knowledge in the cyber-physical systems domain that the tight interaction between the cyber and physical elements provides the possibility of substantially improving the performance of these systems that is otherwise impossible. On the downside, however, this tight interaction with cyber elements makes it easier for an adversary to compromise the safety of the system. This beco

A Self-Aware Epilepsy Monitoring System for Real-Time Epileptic Seizure Detection

Epilepsy is one of the most prevalent paroxystic neurological disorders that can dramatically degrade the quality of life and may even lead to death. Therefore, real-time epilepsy monitoring and seizure detection has become important over the past decades. In this context, wearable technologies offer a promising solution to pervasive epilepsy monitoring by removing the constraints with respect to

Tailoring SVM Inference for Resource-Efficient ECG-Based Epilepsy Monitors

Event detection and classification algorithms are resilient towards aggressive resource-aware optimisations. In this paper, we leverage this characteristic in the context of smart health monitoring systems. In more detail, we study the attainable benefits resulting from tailoring Support Vector Machine (SVM) inference engines devoted to the detection of epileptic seizures from ECG-derived features

Real-time classification technique for early detection and prevention of myocardial infarction on wearable devices

Continuous monitoring of patients suffering from cardiovascular diseases and, in particular, myocardial infarction (MI) places a considerable burden on health-care systems and government budgets. The rise of wearable devices alleviates this burden, allowing for long-term patient monitoring in ambulatory settings. One of the major challenges in this area is to design ultra-low energy wearable devic

Stability-aware integrated routing and scheduling for control applications in Ethernet networks

Real-time communication over Ethernet is becoming important in various application areas of cyber-physical systems such as industrial automation and control, avionics, and automotive networking. Since such applications are typically time critical, Ethernet technology has been enhanced to support time-driven communication through the IEEE 802.1 TSN standards. The performance and stability of contro

Optimization of message encryption for real-time applications in embedded systems

Today, security can no longer be treated as a secondary issue in embedded and cyber-physical systems. Therefore, one of the main challenges in these domains is the design of secure embedded systems under stringent resource constraints and real-time requirements. However, there exists an inherent trade-off between the security protection provided and the amount of resources allocated for this purpo

Personalized Real-Time Federated Learning for Epileptic Seizure Detection

Epilepsy is one of the most prevalent paroxystic neurological disorders. It is characterized by the occurrence of spontaneous seizures. About 1 out of 3 patients have drug-resistant epilepsy, thus their seizures cannot be controlled by medication. Automatic detection of epileptic seizures can substantially improve the patient's quality of life. To achieve a high-quality model, we have to collect d

Control-quality driven task mapping for distributed embedded control systems

Many embedded control systems are implemented on execution platforms with several computation nodes and communication components. Distributed embedded control systems typically comprise multiple control loops that share the available computation and communication resources of the platform. It is well known that such resource sharing leads to complex delay characteristics that degrade the control q

Jfair : A scheduling algorithm to stabilize control applications

Control applications are considered to be among the core applications in cyber-physical and embedded realtime systems, for which jitter is typically an important factor. This paper investigates whether it is possible to guarantee certain amount of jitter for a given set of applications on a shared platform. The effect of jitter on the stability of control applications and its relation with the lat

Analysis and design of real-time servers for control applications

Today, a considerable portion of embedded systems, e.g., automotive and avionic, comprise several control applications. Guaranteeing the stability of these control applications in embedded systems, or cyber-physical systems, is perhaps the most fundamental requirement while implementing such applications. This is different from the classical hard real-time systems where often the acceptance criter

Intrusion-damage assessment and mitigation in cyber-physical systems for control applications

With cyber-physical systems opening to the outside world, security can no longer be considered a secondary issue. One of the key aspects in security of cyber-phyiscal systems is to deal with intrusions. In this paper, we highlight the several unique properties of control applications in cyber-physical systems. Using these unique properties, we propose a systematic intrusion-damage assessment and m

Self-triggered controllers, resource sharing, and hard guarantees

Today, many control applications in embedded and cyber-physical systems are implemented on shared platforms, alongside other hard real-time or safety-critical applications. Having the resource shared among several applications, to provide hard guarantees, it is required to identify the amount of resource needed for each application. This is rather straightforward when the platform is shared among