{"id":13745,"date":"2023-07-06T16:21:16","date_gmt":"2023-07-06T16:21:16","guid":{"rendered":"http:\/\/scannn.com\/what-are-fitbits-sleep-profile-animals-heres-how-they-work\/"},"modified":"2023-07-06T16:21:16","modified_gmt":"2023-07-06T16:21:16","slug":"what-are-fitbits-sleep-profile-animals-heres-how-they-work","status":"publish","type":"post","link":"https:\/\/scannn.com\/lv\/what-are-fitbits-sleep-profile-animals-heres-how-they-work\/","title":{"rendered":"What are Fitbit\u2019s Sleep Profile animals? Here\u2019s how they work"},"content":{"rendered":"<p> <br \/>\n<\/p>\n<div>\n<p data-block-key=\"pgl5b\">Fitbit launched Sleep Profile last year as a Premium feature that gives users a detailed monthly analysis of their sleep after they\u2019ve used the feature for at least 14 nights over a month. \u201cThis was a multi-year effort,\u201d says Fitbit research scientist Karla Gleichauf. \u201cWe started with the research question of, \u2018Are there different types of sleepers?\u2019 There\u2019s been a lot of interest in this question in academia, but not much capability to answer it until wearables.\u201d But the team didn\u2019t only want to figure out different sleep styles; they also wanted to help people sleep better based on that information, Karla explains. So the Fitbit team set out to accumulate some extremely useful data.<\/p>\n<p data-block-key=\"261go\">First, they engineered more than 1,000 sleep features to capture users&#8217; sleeping behaviors in order to determine if there were sleeper types and what those types were. Those sleep features included things like the probability of waking up in the first hour of sleep, sleep cycle length, wake time consistency and weekend versus weekday bedtime discrepancy. Then the team used machine learning technology to cluster the user data and found the answer to their first question: Yes, there are different types of sleepers \u2014 about six types, in fact.<\/p>\n<p data-block-key=\"15omg\">To make this finding useful to people, Fitbit researchers began working with colleagues on Fitbit\u2019s product side. \u201cWe needed to find a way to translate this sort of \u2018mathy\u2019 information about sleep types into something that\u2019s more identifiable,\u201d Karla says.<\/p>\n<p data-block-key=\"27voe\">That led to a bunch of brainstorming about different ways to represent the sleep types, says Elena Perez, a Fitbit product manager. \u201cWe thought about using natural elements \u2014 like maybe a restless sleeper was a stormy ocean,\u201d she says. But in testing this and similar options, the team found that people had a hard time connecting to these representations. The Fitbit crew also didn\u2019t want users to associate anything negative with their Sleep Profiles \u2014 they just wanted to better explain them. Then, they thought about animals.<\/p>\n<p data-block-key=\"36n54\">\u201cWe feel connected to animals, and there aren\u2019t often inherent negative associations with a dolphin or a hedgehog,\u201d Elena explains.<\/p>\n<p data-block-key=\"egp6l\">The team worked with ethnographers and animal experts to determine the right animals for each sleep type (and what they would look like), eventually landing on the bear, the dolphin, the hedgehog, the giraffe, the parrot and the tortoise. They also dove deeper into the data to figure out how many and what kinds of sleep types would be best to help people learn about their sleep health.<\/p>\n<\/div>\n<p><br \/>\n<br \/><a href=\"https:\/\/blog.google\/products\/fitbit\/fitbit-sleep-profile-animals\/\">Source link <\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Fitbit launched Sleep Profile last year as a Premium feature that gives users a detailed monthly analysis of their sleep after they\u2019ve used the feature for at least 14 nights over a month. \u201cThis was a multi-year effort,\u201d says Fitbit research scientist Karla Gleichauf. \u201cWe started with the research question of, \u2018Are there different types [&hellip;]<\/p>\n","protected":false},"author":16,"featured_media":13746,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[100],"tags":[],"class_list":["post-13745","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-google"],"_links":{"self":[{"href":"https:\/\/scannn.com\/lv\/wp-json\/wp\/v2\/posts\/13745","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/scannn.com\/lv\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/scannn.com\/lv\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/scannn.com\/lv\/wp-json\/wp\/v2\/users\/16"}],"replies":[{"embeddable":true,"href":"https:\/\/scannn.com\/lv\/wp-json\/wp\/v2\/comments?post=13745"}],"version-history":[{"count":0,"href":"https:\/\/scannn.com\/lv\/wp-json\/wp\/v2\/posts\/13745\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/scannn.com\/lv\/wp-json\/wp\/v2\/media\/13746"}],"wp:attachment":[{"href":"https:\/\/scannn.com\/lv\/wp-json\/wp\/v2\/media?parent=13745"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/scannn.com\/lv\/wp-json\/wp\/v2\/categories?post=13745"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/scannn.com\/lv\/wp-json\/wp\/v2\/tags?post=13745"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}