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Empatica's wearables, Embrace2 and E4, track physiological signals such as Heart Rate Variability, electrodermal activity, acceleration and movement, skin temperature, and autonomic arousal. [3] Embrace2 has been cleared by the FDA as a seizure alerting solution for epilepsy patients with generalized tonic-clonic seizures . [ 4 ]
[3] Others use different terms for this construct or very similar constructs. Especially popular—perhaps more popular than "empathic concern"—are sympathy, compassion, or pity. [4] Other terms include the tender emotion and sympathetic distress. [5] People are strongly motivated to be connected to others. [6]
The planet, HD 76920 b, is an eccentric Jupiter with a minimum mass of 3.57 M J [3] and a very high orbital eccentricity of 0.8782, [7] which at the time of discovery made it the most eccentric known planet orbiting an evolved star.
Rosalind Wright Picard (born 1962) [1] is an American scholar and inventor who is Grover M. Hermann Professor of Health Sciences and Technology at MIT, founder and director of the Affective Computing Research Group at the MIT Media Lab, and co-founder of the startups Affectiva [2] and Empatica. [3]
A/RES/66/2 Plenary 117 19 September 2011 APPROVED Political declaration of the High-level Meeting of the General Assembly on the Prevention and Control of Non-communicable Diseases without vote [3] A/RES/66/3 Plenary 67 (b) 22 September 2011 APPROVED United against racism, racial discrimination, xenophobia and related intolerance without vote
66 Ophiuchi is a binary [6] variable star [13] in the equatorial constellation of Ophiuchus. It has the variable star designation V2048 Ophiuchi , while 66 Ophiuchi is the Flamsteed designation . This object is visible to the naked eye as a faint, blue-white hued point of light with a baseline apparent visual magnitude of 4.60. [ 2 ]
The Red Sox's ballyhooed signing of Alex Bregman was met with considerable resistance Monday when Rafael Devers said he wouldn't cede third base. “Third base is my position,” Devers said ...
Dex-net includes a high-resolution 3-D sensor and two arms, each controlled by a different neural network. One arm is equipped with a conventional robot gripper and another with a suction system. The robot’s software scans an object and then asks both neural networks to decide, on the fly, whether to grab or suck a particular object.