Can wifi signals be used to read lips?

Question

This Atlantic article claims that researchers have been able to do numerous high-level diagnostics by analyzing disruptions in wifi signal fields, including identifying individuals and reading lips:

As people move through a space with a Wi-Fi signal, their bodies affect it, absorbing some waves and reflecting others in various directions. By analyzing the exact ways that a Wi-Fi signal is altered when a human moves through it, researchers can “see” what someone writes with their finger in the air, identify a particular person by the way that they walk, and even read a person’s lips with startling accuracy—in some cases even if a router isn’t in the same room as the person performing the actions.

Is this true?

Answer 1

The Atlantic article in the question provides references to support its claims:

And a group of researchers led by a Berkeley Ph.D. student presented technology at a 2014 conference that could “hear” what people were saying by analyzing the distortions and reflections in Wi-Fi signals created by their moving mouths. The system could determine which words from a list of lip-readable vocabulary were being said with 91 percent accuracy when one person was speaking, and 74 percent accuracy when three people were speaking at the same time.

That link points to the details of a 2016 article, We Can Hear You with Wi-Fi! (available here as a PDF) which describes the prototype project consistently with the Atlantic article:

This paper presents WiHear, a novel system that enables Wi-Fi signals to hear talks. WiHear is compatible with existing Wi-Fi standards and can be extended easily to commercial Wi-Fi products. To achieve lip reading, WiHear introduces a novel system for sensing and recognizing micromotions (e.g. mouth movements). WiHear consists of two key components, mouth motion profile for extracting features, and learning-based signal analysis for lip reading. Further, Mouth motion profile is the first effort that leverage partial multipath effects to get the whole mouth motions’ impacts on radio. Extensive experiments demonstrate that WiHear can achieve recognition accuracy of 91% for single user speaking no more than 6 words and up to 74% for hearing no more than 3 users simultaneously.