According to World Health Organization, there is an estimated 2.2 billion people with a near or distance vision impairment worldwide. Difficulty in self-navigation is one of the greatest challenges to independence for the blind and low vision (BLV) people. Through consultations with several BLV service providers, we realized that negotiating surface discontinuities is one of the very prominent challenges when navigating an outdoor environment within the urban. Surface discontinuities are commonly formed by rises and drop-offs along a pathway. They could be a threat to balancing during a walk and perceiving such a threat is highly challenging to the BLVs.

After a first date it's normal to wonder if those warm, fuzzy feelings are reciprocated. Now, experts are one step closer to an app that will tell you if they're'just not that into you'. Researchers have trained a computer - using data from wearable technology that measures respiration, heart rates and perspiration – to identify the type of conversation two people are having. In experiments with 16 pairs of participants, it was able to differentiate four different conversation scenarios with as much as 75 per cent accuracy. Lead author Iman Chatterjee, from the University of Cincinnati, said the technology could one day give you honest feedback about yourself or your date.

Machine Learning (ML) algorithms are generally designed for scenarios in which all data is stored in one data center, where the training is performed. However, in many applications, e.g., in the healthcare domain, the training data is distributed among several entities, e.g., different hospitals or patients' mobile devices/sensors. At the same time, transferring the data to a central location for learning is certainly not an option, due to privacy concerns and legal issues, and in certain cases, because of the communication and computation overheads. Federated Learning (FL) is the state-of-the-art collaborative ML approach for training an ML model across multiple parties holding local data samples, without sharing them. However, enabling learning from distributed data over such edge Internet of Things (IoT) systems (e.g., mobile-health and wearable technologies, involving sensitive personal/medical data) in a privacy-preserving fashion presents a major challenge mainly due to their stringent resource constraints, i.e., limited computing capacity, communication bandwidth, memory storage, and battery lifetime. In this paper, we propose a privacy-preserving edge FL framework for resource-constrained mobile-health and wearable technologies over the IoT infrastructure. We evaluate our proposed framework extensively and provide the implementation of our technique on Amazon's AWS cloud platform based on the seizure detection application in epilepsy monitoring using wearable technologies.

Falls among the elderly are a major health concern, frequently resulting in serious injuries and a reduced quality of life. In this paper, we propose "BlockTheFall," a wearable device-based fall detection framework which detects falls in real time by using sensor data from wearable devices. To accurately identify patterns and detect falls, the collected sensor data is analyzed using machine learning algorithms. To ensure data integrity and security, the framework stores and verifies fall event data using blockchain technology. The proposed framework aims to provide an efficient and dependable solution for fall detection with improved emergency response, and elderly individuals' overall well-being. Further experiments and evaluations are being carried out to validate the effectiveness and feasibility of the proposed framework, which has shown promising results in distinguishing genuine falls from simulated falls. By providing timely and accurate fall detection and response, this framework has the potential to substantially boost the quality of elderly care.

Turning the page on 2022 will be a cause for celebration in the healthcare sector. The past year was one of the worst financial years on record for hospitals, according to Kaufman Hall. New data from the healthcare consulting firm and the American Hospital Association indicates that 53% to 68% of the nation's hospitals will end 2022 in the red. At the same time, hospital employment is down approximately 100,000 from pre-pandemic levels. This is all happening amid a backdrop of growing margin pressures and an aging population.

Nellore: The conference on Futuristic Nursing being held at Narayana Nursing College here has discussed at length aspects of patient safety as also use of artificial intelligence and tele-medicine, apart from mobile health and sensor-based technologies (smartphones, smartphone apps and wearable technologies). More than 800 nurses are participating in the meet and around 40 eminent nursing leaders across the globe discussing the latest in nursing practices during the 3-day conference from Saturday. In a paper on'Artificial Intelligence in Nursing' presented jointly by Dr Ramesh M.Sc Phd, HoD Medical Surgical Nursing, St Paul's Hospital Millennium Medical College, Ethiopia, and Dr S. Indira, Dean of Narayana Nursing College, said AI offers three advantages over traditional methods -- the ability to quickly consider large volumes of data in risk prediction, increased intervention specificity (accurately flagging patients most at-risk) and automated adjustments in variable selection and calculation. "AI can help detect which patient features are most important in public health applications, allowing for more focused preventive interventions. Robots may aid nursing care tasks in hazardous clinical environments and they have the potential to automate some tasks."

Apple's Watch Ultra, with its 2000-nit digital display and GPS capabilities, is a far cry from its Revolutionary War-era self-winding forebears. What sorts of wondrous body-mounted technologies might we see another hundred years hence? In his new book, The Skeptic's Guide to the Future, Dr. Steven Novella (with assists from his brothers, Bob and Jay Novella) examines the history of wearables and the technologies that enable them to extrapolate where further advances in flexible circuitry, wireless connectivity and thermoelectric power generation might lead. Excerpted from the book The Skeptics' Guide to the Future: What Yesterday's Science and Science Fiction Tell Us About the World of Tomorrow by Dr. Steven Novella, with Bob Novella and Jay Novella. As the name implies, wearable technology is simply technology designed to be worn, so it will advance as technology in general advances.

The rapid growth of the Internet of Things (IoT) has been fuelled by the falling cost of sensors, the proliferation of connected devices, and the advancement of artificial intelligence (AI). The IoT is the network of physical objects (vehicles, devices, buildings, etc.) embedded with sensors, software, electronics, and network connectivity that allows these objects to collect and exchange data. According to a recent report from McKinsey, the IoT could have a total economic impact of up to $12.6 trillion per year by 2030. While the IoT is still in its infancy, the AIoT represents the next wave of the IoT, where AI is used to turn data into insights and actions. The AIoT has the potential to transform industries and society, and it is already starting to have an impact.

The healthcare sector experienced transition as a result of COVID-19, and this shift will last for years to come. Despite industry obstacles, the pandemic has led to a growing acceptance of new technology among patients, providers, and healthcare practitioners. These technologies lessen workplace stress and improved patient care. But there is still hope for change. Many medical schools now include the use of technology in their curriculum; the new generation of medical practitioners has a distinct relationship with technology.

We are able to turn on the lights in our homes from a desk in an office miles away. The built-in cameras and sensors embedded in our refrigerator let us easily keep tabs on what is present on the shelves, and when an item is close to expiration. When we get home, the thermostat has already adjusted the temperature so that it's lukewarm or brisk, depending on our preference. These are not examples from a futuristic science fiction story. These are only a few of the millions of frameworks part of the Internet of Things (IoT) being deployed today.