In Affective computing, recognizing users' emotions accurately is the basis of affective human-computer interaction. Understanding users' interoception contributes to a better understanding of individually different emotional abilities, which is essential for achieving inter-individually accurate emotion estimation. However, existing interoception measurement methods, such as the heart rate discrimination task, have several limitations, including their dependence on a well-controlled laboratory environment and precision apparatus, making monitoring users' interoception challenging. This study aims to determine other forms of data that can explain users' interoceptive or similar states in their real-world lives and propose a novel hypothetical concept "cyberoception," a new sense (1) which has properties similar to interoception in terms of the correlation with other emotion-related abilities, and (2) which can be measured only by the sensors embedded inside commodity smartphone devices in users' daily lives. Results from a 10-day-long in-lab/in-the-wild hybrid experiment reveal a specific cyberoception type "Turn On" (users' subjective sensory perception about the frequency of turning-on behavior on their smartphones), significantly related to participants' emotional valence. We anticipate that cyberoception to serve as a fundamental building block for developing more "emotion-aware", user-friendly applications and services.

Resting heart rate (RHR) is an important biomarker of cardiovascular health and mortality, but tracking it longitudinally generally requires a wearable device, limiting its availability. We present PHRM, a deep learning system for passive heart rate (HR) and RHR measurements during everyday smartphone use, using facial video-based photoplethysmography. Our system was developed using 225,773 videos from 495 participants and validated on 185,970 videos from 205 participants in laboratory and free-living conditions, representing the largest validation study of its kind. Compared to reference electrocardiogram, PHRM achieved a mean absolute percentage error (MAPE) < 10% for HR measurements across three skin tone groups of light, medium and dark pigmentation; MAPE for each skin tone group was non-inferior versus the others. Daily RHR measured by PHRM had a mean absolute error < 5 bpm compared to a wearable HR tracker, and was associated with known risk factors. These results highlight the potential of smartphones to enable passive and equitable heart health monitoring.

If you spend too much time on your smartphone, scientists have a list of 10 solutions that can help you cut back on screen time. The small but effective changes can help curb smartphone addiction and mental health issues such as depression, say experts at McGill University in Canada. In experiments, people following the strategies reduced their screen time, felt less addicted to their phone and improved their sleep quality, the experts report. Among the 10 strategies are changing the phone display to'greyscale' so the display appears black and white, and disabling facial recognition as a method of unlocking the screen. A black and white screen makes smartphones'less gratifying' to look at compared to the bright colours offered by app icons such as TikTok and Instagram.

Looking at your phone makes other people nearby do the same in less than a minute, a new study reveals. Researchers in Italy investigated human'mimicry' or the'chameleon effect' – subconsciously replicating the physical actions of another human. Out of 184 people, half replicated the action of touching and looking at their phone 30 seconds after a subconscious trigger, researchers found. The experts say copying smartphone use is similar to the well-known'contagious yawning' phenomenon, when an individual yawns in response to someone else doing so. Mammals have evolved to subconsciously mimic each others' behaviour without knowing it.

On Monday, the nascent self-driving vehicle sector reached an unfortunate milestone when, for the first time, a self-driving car killed a pedestrian in Tempe, Arizona. This also means robot drivers are becoming more like their human predecessors--who kill thousands of pedestrians every year. And that number has risen dramatically in the past several years. In 2016, cars hit and killed nearly 6,000 pedestrians. The Great Recession explains some of the fluctuation.

South Korean Go players will be banned from using smartphones during official tournaments in the future, and it's all thanks to Google's AlphaGo AI. The Korea Times reports that the Korea Baduk Association -- baduk being the local name for Go -- is currently drafting new rules that will outlaw smartphone use in matches. While the organization is fully aware you can't carry AlphaGo around in your pocket at the moment, it's preempting a time when certain AI tools that can give players a competitive edge do become available on smartphones. It may seem strange that smartphone use is permitted in official Go competitions as it stands, but then there's basically no precedent for digital tools being of any help to experienced players. Though IBM's Deep Blue chess computer beat world champ Garry Kasparov in 1997, the number of variables and strategic complexity of Go have kept programmers from creating bots that exhibit anything more than an amateur skill level.