A Voting-Enhanced Dynamic-Window-Length Classifier for SSVEP-Based BCIs.

We present a dynamic window-length classifier for steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) that does not require the user to choose a feature extraction method or channel set. Instead, the classifier uses multiple feature extraction methods and channel selections to infer the SSVEP and relies on majority voting to pick the most likely target. The classifier extends the window length dynamically if no target obtains the majority of votes.

Federated Learning in Smart City Sensing: Challenges and Opportunities.

Smart Cities sensing is an emerging paradigm to facilitate the transition into smart city services. The advent of the Internet of Things (IoT) and the widespread use of mobile devices with computing and sensing capabilities has motivated applications that require data acquisition at a societal scale. These valuable data can be leveraged to train advanced Artificial Intelligence (AI) models that serve various smart services that benefit society in all aspects.

A Survey of Healthcare Internet-of-Things (HIoT): A Clinical Perspective.

In combination with current sociological trends, the maturing development of IoT devices is projected to revolutionize healthcare. A network of body-worn sensors, each with a unique ID, can collect health data that is orders-of-magnitude richer than what is available today from sporadic observations in clinical/hospital environments. When databased, analyzed, and compared against information from other individuals using data analytics, HIoT data enables the personalization and modernization of care with radical improvements in outcomes and reductions in cost.

Home use of a compact, 12‑lead ECG recording system for newborns.

Background: An easy-to-operate ECG recorder should be useful for newborn screening for heart conditions, by health care workers - or parents. We developed a one-piece electrode strip and a compact, 12‑lead ECG recorder for newborns.

Method: We enrolled 2582 newborns in a trial to assess abilities of parents to record a 12‑lead ECG on their infants (2-4 weeks-old).

Emerging Security Mechanisms for Medical Cyber Physical Systems.

The following decade will witness a surge in remote health-monitoring systems that are based on body-worn monitoring devices. These Medical Cyber Physical Systems (MCPS) will be capable of transmitting the acquired data to a private or public cloud for storage and processing. Machine learning algorithms running in the cloud and processing this data can provide decision support to healthcare professionals.

"QT clock" to improve detection of QT prolongation in long QT syndrome patients.

Background: The QT interval is a risk marker for cardiac events such as torsades de pointes. However, QT measurements obtained from a 12-lead ECG during clinic hours may not capture the full extent of a patient's daily QT range.

Objective: The purpose of this study was to evaluate the utility of 24-hour Holter ECG recording in patients with long QT syndrome (LQTS) to identify dynamic changes in the heart rate-corrected QT interval and to investigate methods of visualizing the resulting datasets.

Cloud-based privacy-preserving remote ECG monitoring and surveillance.

Background: The number of technical solutions for monitoring patients in their daily activities is expected to increase significantly in the near future. Blood pressure, heart rate, temperature, BMI, oxygen saturation, and electrolytes are few of the physiologic factors that will soon be available to patients and their physicians almost continuously. The availability and transfer of this information from the patient to the health provider raises privacy concerns.