Electrodermal activity (EDA) provides a direct indicator of sympathetic nervous system arousal through changes in skin conductance. However, wearable EDA sensing poses challenges such as inconsistent skin contact, electrode impedance variability, motion artifacts, and power constraints. To address these issues, this study presents mobile EDA (mEDA), a compact device driven by a stabilized direct-current source. A validation study was conducted on ten healthy adult participants in a time-synchronized protocol to collect data from BIOPAC and mEDA concurrently. mEDA recordings employed gel electrodes for P1-P5 and dry (textile) electrodes for P6-P10, while the BIOPAC MP160 system used gel electrodes for all participants. Participants underwent a 30-minute protocol of resting, deep breathing, and three cognitive tasks. The preprocessing pipeline consisted of low-pass filter and artifact (sharp peaks and flat line) removal. Cleaned signals were converted into frequency domain components for decomposition into low and high frequency components, skin conductance level (SCL), and skin conductance response (SCR) respectively. SCL and SCR were converted back to the time domain to analyze performance metrics between both devices. Pearson correlation, coherence, and Dynamic Time Warping (DTW) were computed on SCL, while zero-crossing peaks were counted for SCR analysis. With gel electrodes, the average Pearson correlation was 0.92 and the SCR peak count difference was 38. For textile electrodes, the correlation was 0.88 with a peak count difference of 119. Both configurations achieved coherence above 0.95 and DTW below 0.5 for most participants. These results demonstrate mEDA's reliable performance in capturing both tonic and phasic EDA across electrode configurations.

A neonatal intensive care unit (NICU) provides an optimal environment for the care of preterm babies. Bedside nurses are fundamental to this care provided to preterm babies in the NICU. Modern NICUs are technology-intensive space, instrumented with several monitoring technologies to help the nurses track the babies in their care. These technologies help the nurses in a way that is essential for the successful operation of the NICU. To understand how these monitoring technologies function in the NICU from the viewpoint of the nurses, we conducted semi-structured interviews with seven nurses who work at a NICU in the US. We then performed a thematic analysis on the interviews and we found that, despite the utility of the monitoring technologies, they also pose several challenges to the nurses in performing their duties. More specifically, we discovered that: (1) all elements of the monitoring technologies posed a challenge in some way; (2) in a few specific situations, the nurses were able to make up for some of these challenges; and (3) the nurses suggested improvements to all elements of the monitoring technologies. Based on these findings, we describe six areas of future research that argue for the design of monitoring technologies as a way to empower nurses. These include: improved vital signs monitoring that facilitate kangaroo care, using voice to manage alarms, video feeds controlled by nurses in the patient rooms, giving more control over the alarm sounds to the nurses, having a common interface and leveraging augmented reality to help the nurses control the monitoring technologies.

Recent years have seen a proliferation of security-focused smart home devices (SSHDs). SSHDs, such as smart locks and cameras, are designed to accomplish critical tasks, such as protecting one’s home and property. However, their use by and for people with disabilities (PwD) has not been broadly investigated. To explore the state of SSHD use by PwD, we collected 114,871 amazon.com reviews for popular SSHDs and created a data set of reviews pertaining to PwD. We performed a broad analysis of the reviews in this data set and found that the presence of SSHDs empowered PwD to secure their domiciles independently. Further, caregivers used SSHDs to monitor PwD, ostensibly for the latter’s safety, albeit without explicit consent. Moreover, we also found that SSHDs have several drawbacks that impose various barriers of use on PwD. We analyze the significance of these findings and suggest five future research opportunities for SSHD design.

In the US people with intellectual and developmental disabilities (I/DD) comprise one of the most likely groups to experience traumatic life events. These experiences often produce negative effects (e.g., stress, anxiety, grief, numbing, etc.) that need to be managed. Methods such as emotional self-regulation are often used to help people cope when these effects present themselves post-trauma. In recent years mobile-computing-devices-based apps have been increasingly used to help the general population with autonomous self-regulation. However, none of these is designed for people with I/DD or is cognizant of the trauma they experience in their lives. We interviewed eight (8) practitioners at a trauma services organization that, among other things, helps people with I/DD learn and practice post-trauma self-regulation. The goal of the interviews is to understand what it would take to build post-trauma self-regulation apps for people with I/DD. Based on the interview responses we argue for a set of guidelines, based on the social work practice of trauma-informed care, to design post-trauma self-regulation apps for people with I/DD.

In the US, the abuse of individuals with intellectual and developmental disabilities (I/DD) is at epidemic proportions; however, the reporting of such abuse has been severely lacking. It has been found that individuals with I/DD are more aware of when and how to report abuse if they have received abuse prevention training. Consequently, in this paper we present the design of a mobile-computing app called Recognize to teach individuals with I/DD about abuse. Our research team is diverse, with both individuals with I/DD and neurotypical individuals. We leveraged this diversity by utilizing a co-design process with our team members who live with I/DD. Our team developed three initial prototypes of the app and performed a qualitative, within-group user study with six separate individuals with I/DD who are themselves experienced teachers to other individuals with I/DD. We found that, overall, the app would be viable for use by individuals with I/DD. We end the paper with a brief discussion of the implications of our findings toward building a full prototype of the app.

Incidents of abuse committed against persons with intellectual and developmental disabilities (I/DD) are woefully under-reported. One way of helping change this situation is to empower persons with I/DD with tools to self-report abuse. During abuse reporting the reporter is requested to provide a variety of information about the abuse and its context. In this paper wanted to understand which pieces of information are typically needed to successfully report abuse and whether persons with I/DD can provide them. Consequently, we conducted an exploratory survey of the staff at an adult protective services agency in our region and asked them about their experiences with receiving abuse self-reports by persons with I/DD. Overall, we found that persons with I/DD are typically able to provide enough information to successfully self-report abuse.

Authentication has become increasingly ubiquitous for controlling access to personal computing devices (e.g., laptops, tablets, and smartphones). In this paper, we aim to understand the authentication process used by people with upper extremity impairment (UEI). A person with UEI lacks range of motion, strength, endurance, speed, and/or accuracy associated with arms, hands, or fingers. To this end, we conducted semi-structured interviews with eight (8) adults with UEI about their use of authentication for their personal computing devices. We found that our participants primarily use passwords and PINs as a verification credential during authentication. We found the process of authentication to have several accessibility issues for our participants. Consequently, our participants implemented a variety of workarounds that prioritized usability over security throughout the authentication process. Based on these findings, we present six broad subareas of research that should be explored in order to create more accessible authentication for people with UEI.

In the US, abuse of individuals with intellectual and developmental disabilities (I/DD) is at epidemic proportions. Further, abuse incidents of individuals with I/DD are woefully under-reported. We surveyed practitioners who help individuals with I/DD post-abuse to get a broader context on the problem. We found that abuse of individuals with I/DD was often reported by someone other than the survivor, as survivors faced impediments in reporting. Consequently, we argue for developing a mobile-computing-based reporting tool for empowering individuals with I/DD to self-report abuse. Next, we conducted focus groups of individuals with I/DD to evaluate the tool’s viability, with respect to their ability to recognize/report abuse and use mobile-computing devices. We found individuals with I/DD could recognize/report abuse well when they received appropriate training. We also found individuals with I/DD could independently use their devices, though they shared access to them with family. Based on these findings, we call for several lines of accessibility research in designing an abuse self-reporting tool for individuals with I/DD.

Recent years have seen the emergence of wearable medical systems (WMS) that have demonstrated great promise for improved health monitoring and overall well-being. Ensuring that these WMS accurately monitor a user’s current health state is crucial. This is especially true in the presence of adversaries who want to mount data manipulation attacks on the WMS. The goal of data manipulation attacks is to alter the measurements made by the sensors in the WMS with fictitious data that is plausible but not accurate. Such attacks force clinicians or any decision support system AI, analyzing the WMS data, to make incorrect diagnosis and treatment decisions about the patient’s health. In this paper, we present an approach to detect data manipulation attacks based on the idea that multiple physiological signals based on the same underlying physiological process (e.g., cardiac process) are inherently related to each other. We capture the commonalities between a “target” sensor measurement and another “reference” sensor measurement (which is trustworthy), by building an image reconstruction-based classifier and using this classifier to identify any unilateral changes in the target sensor measurements. This classifier is user-specific and needs to be created for every user on whom the WMS is deployed. In order to showcase our idea, we present a case study where we detect data manipulation attacks on electrocardiogram (ECG) sensor measurements in a WMS using blood pressure measurement as reference. We chose ECG and blood pressure—in arterial blood pressure (ABP) form—because both are some of the most commonly measured physiological signals in a WMS environment. Our approach demonstrates promising results with above 98% accuracy in detecting even subtle ECG alterations for both healthy subjects and those with different cardiac ailments. Finally, we show that the approach is general in that it can be used to build a model for detecting data manipulation attacks that alter ABP sensor measurements using the ECG sensor as reference.

In this paper, we present an approach to detecting signal injection-based morphological alterations of ECG measurements in Body Sensor Networks (BSN). Signal injection attacks target, the usually unprotected, analog sensing interface of the sensors in a BSN and induce arbitrary signals in them. Signal injection is very dangerous because can be stealthily mounted on unsuspecting BSN users from close proximity (for example in a public place). Inducing morphological alterations in ECG measurements can have profound consequences for the user, as an adversary can easily make a person who is experiencing cardiac arrhythmia appear to be normal and thus cause immediate or long-term harm to their health. To detect signal injection-based morphological alterations, we leverage the idea that multiple physiological signals based on the same underlying physiological process (e.g., cardiac process) are inherently related to each other, i.e., have common features. Any adversarial alteration of one of the signals will not be reflected in the other signal(s) in the group. Therefore, to detect the morphological alterations in ECG measurements, we use arterial blood pressure (ABP) measurements. Both ECG and ABP measurements are alternative representation of the cardiac process. Our approach demonstrates promising results with over 90% accuracy in detecting even subtle ECG morphological alterations for both healthy subjects and those with cardiac conditions.

Body Sensor Network (BSN) -- a network of body-worn wireless health monitoring sensors -- have a tremendous potential to remove the space and time restrictions on health management. Given the importance of the data BSNs collect for improved health outcomes, securing the data from unauthorized tampering is essential. A compromised (or externally influenced) sensor in a BSN may generate erroneous patient data leading to, among other things, wrong diagnosis and treatment. In this paper, we present a novel approach to address the problem of detecting maliciously induced morphological alterations in the ECG signal (i.e., inducing changes to its shape). Our approach works by correlating the ECG signals with synchronously measured arterial blood pressure (ABP) signal measured using a distinct (and un-compromised) sensor. Initial analysis of our system demonstrates promising results, with 99.75% accuracy in detecting ECG signal morphological alterations for healthy patients with normal sinus rhythms.

The articles in this special section are focused on two major aspects of Internet of things (IoT) technologies for smart and connected health services (SCH): 1) monitoring and assisting individuals by means of smart systems including sensors, devices, and robotics; and 2) creating interoperable digital health information infrastructures to increase medical/health information availability and use. The papers published in this SI provide evidence that SCH tools that rely upon IoT technologiescould significantly improve clinical outcomes and thequality of life of individuals undergoing monitoring.

The article presents an access control model called Criticality Aware Access Control (CAAC) for criticality (emergency) management in smart infrastructures. Criticalities are consequences of events which take a system (in our case, a smart infrastructure) into an unstable state. They require the execution of specific response actions in order to bring them under control. The principal aim of CAAC is to grant the right set of access privileges (to facilitate response action execution), at the right time, to the right set of subjects, for the right duration, in order to control the criticalities within the system. In this regard, the CAAC model uses a stochastic model called the Action Generation Model to determine the required response actions for the combination of criticalities present within the system. It then facilitates response actions by adaptively altering the privileges to specific subjects, in a proactive manner, without the need for any explicit access requests. In this article, we formalize the CAAC model and validate it based on two design goals - proactivity and adaptiveness. Finally, we present a case study demonstrating CAAC’s operation on an oil-rig platform in order to aid in the response to health- and fire-related criticalities.

Observing the success of the open source software movement, the Adaptive Vehicle Make (AVM) is a program run by the Defense Advanced Project Agency (DARPA) with the goal of applying crowd-sourced and component-based engineering to the design of military vehicles. In this paper, we present a credentialing system called TrustForge, which enables effective and flexible access control for the AVMcrowd-sourced repository. Credentialing systems are essential in crowdsourcing to ensure quality, since it is potentially open to contributions made by anyone. The open source software community has developed elaborate manual approaches of managing its contributor community, which are often very labor-intensive and inefficient. Our aim with TrustForge is to improve the automation of the credentialing and access control process in the context of component-based systems, where users contribute components at various levels of abstraction. TrustForge takes a hybrid approach that combines trust policy and reputation to address this problem. In TrustForge, a policy language is used to specify the access control rules for users in the system to contribute components. In addition, reputation values computed for users based on the quality of their past component contributions are used to tune the static policies to enable flexibility and adaptiveness. The contributions of this work are as follows: (1) the design of TrustForge - an effective and flexible access control mechanism that combines policy and reputation approaches; (2) the identification of heuristics for component quality measurement and a novel reputation computation algorithm for evaluating user trustworthiness; (3) a data model based on provenance graphs that allows efficient repository information storage and retrieve. We have implemented TrustForge system and integrate it with the VehicleForge repository system to support the operation of the AVM challenge program. The evaluation results based on realworld deployment and systematic simulation demonstrate that TrustForge can effectively discern the trustworthiness of users within the crowd-sourced system.

Cyber-physical systems (CPSs) couple their cyber and physical parts to provide mission-critical services, including automated pervasive health care, smart electricity grid, green cloud computing, and surveillance with unmanned aerial vehicles (UAVs). CPSs can use the information available from the physical environment to provide such ubiquitous, energy-efficient and low-cost functionalities. Their operation needs to ensure three key properties, collectively referred to as S3: 1) safety: avoidance of hazards; 2) security: assurance of integrity, authenticity, and confidentiality of information; and 3) sustainability: maintenance of long-term operation of CPSs using green sources of energy. Ensuring S3 properties in a CPS is a challenging task given the spatio-temporal dynamics of the underlying physical environment. In this paper, the formal underpinnings of recent CPS S3 solutions are aligned together in a theoretical framework for cyber-physical interactions, empowering CPS researchers to systematically design solutions for ensuring safety, security, or sustainability. The general applicability of this framework is demonstrated with various exemplar solutions for S3 in diverse CPS domains. Further, insights are provided on some of the open research problems for ensuring S3 in CPSs.

Medical cyber-physical systems (MCPS) are life-critical, context-aware, networked systems of medical devices. These systems are increasingly used in hospitals to provide high-quality continuous care for patients. The need to design complex MCPS that are both safe and effective has presented numerous challenges, including achieving high assurance in system software, intoperability, context-aware intelligence, autonomy, security and privacy, and device certifiability. In this paper, we discuss these challenges in developing MCPS, some of our work in addressing them, and several open research issues.

We examine the problem of reliable networked control when the communication channel between the controller and the actuator periodically drops packets and is faulty (i.e., corrupts/alters data). We first examine the use of a standard triple modular redundancy scheme (where the control input is sent via three independent channels) with majority voting to achieve mean square stability. While such a scheme is able to tolerate a single faulty channel when there are no packet drops, we show that the presence of lossy channels prevents a simple majority-voting approach from stabilizing the system. Moreover, the number of redundant channels that are required in order to maintain stability under majority voting increases with the probability of packet drops. We then propose the use of a reputation management scheme to overcome this problem, where each channel is assigned a reputation score that predicts its potential accuracy based on its past behavior. The reputation system builds on the majority voting scheme and improves the overall probability of applying correct (stabilizing) inputs to the system. Finally, we provide analytical conditions on the probabilities of packet drops and corrupted control inputs under which mean square stability can be maintained, generalizing existing results on stabilization under packet drops.

A body area network (BAN) is a wireless network of health monitoring sensors designed to deliver personalized healthcare. Securing intersensor communications within BANs is essential for preserving not only the privacy of health data, but also for ensuring safety of healthcare delivery. This paper presents physiological-signal-based key agreement (PSKA), a scheme for enabling secure intersensor communication within a BAN in a usable (plug-n-play, transparent) manner. PSKA allows neighboring nodes in a BAN to agree to a symmetric (shared) cryptographic key, in an authenticated manner, using physiological signals obtained from the subject. No initialization or predeployment is required; simply deploying sensors in a BAN is enough to make them communicate securely. Our analysis, prototyping, and comparison with the frequently used Diffie-Hellman key agreement protocol shows that PSKA is a viable intersensor key agreement protocol for BANs.

A Body Sensor Network (BSN) is a network of economically powered, wireless, wearable, and implanted health monitoring sensors, designed to continually collect and communicate health information from the host they are deployed on. Due to the sensitive nature of the data collected, securing BSNs is important for privacy preservation and protecting the host from bodily harm. In this article, we present Physiological Value-based Security (PVS), a usable and efficient way of securing intersensor communication schemes for BSNs. The PVS scheme distributes the key used for securing a particular message along with the message itself, by hiding it using physiological values. In this way, it not only eliminates the need for any explicit key distribution, but also reduces the number of keys required at each node to meet all its secure communication requirements. We further demonstrate the use of the PVS scheme in securing cluster topology formation in BSNs. Traditional protocols for cluster formation do not consider security and are therefore susceptible to malicious attacks. We present a PVS-based cluster formation protocol which mitigates these attacks. Performance analysis of the protocol shows that compared to cluster formation protocols secured with non-PVS-based key distribution schemes, it performs efficiently.

A generic theoretical framework for managing critical events in ubiquitous computing systems is presented. The main idea is to automatically respond to occurrences of critical events in the system and mitigate them in a timely manner. This is different from traditional fault-tolerance schemes, where fault management is performed only after system failures. To model the critical event management, the concept of criticality, which characterizes the effects of critical events in the system, is defined. Each criticality is associated with a timing requirement, called its window-of-opportunity, that needs to be fulfilled in taking mitigative actions to prevent system failures. This is in addition to any application-level timing requirements.The criticality management framework analyzes the concept of criticality in detail and provides conditions which need to be satisfied for a successful multiple criticality management in a system. We have further simulated a criticality aware system and its results conform to the expectations of the framework.

Access control policies define the rules for accessing system resources. Traditionally, these are designed to take a reactive view for providing access, based on explicit user request. This methodology may not be sufficient in the case of critical events (emergencies) where automatic and timely access to resources may be required to facilitate corrective actions. This paper introduces the novel concept of criticality which measures the level of responsiveness for taking such actions. The paper further incorporates criticality in an access control framework for facilitating the management of critical situations. Specific properties and requirements for such criticality aware access control are identified and a sample model is provided along with its verification