https://smeragliuolo.io Anna Smeragliuolo Wed, 04 Mar 2020 01:24:32 +0000 https://smeragliuolo.io en https://smeragliuolo.io/Home Wed, 30 Jan 2019 19:26:47 +0000 Anna Smeragliuolo https://smeragliuolo.io/Home I’m Anna. I’m an interaction designer with a background in telemedicine (among other things). I am constantly on the lookout for opportunities to generate connections between new technology and humans, be it through products, immersive experiences, speculative design, or new realities. https://smeragliuolo.io/Thumbnails Wed, 30 Jan 2019 19:26:44 +0000 Anna Smeragliuolo https://smeragliuolo.io/Thumbnails https://smeragliuolo.io/AR-js-studio-an-AR-platform Wed, 04 Mar 2020 01:24:32 +0000 Anna Smeragliuolo https://smeragliuolo.io/AR-js-studio-an-AR-platform an AR platform:AR.js Studioan MVP interface for creating web-based AR experiences created by Swallow Twice <img width="2000" height="2000" width_o="2000" height_o="2000" data-src="https://freight.cargo.site/t/original/i/651e52a607cb5607c6c66b1ae409e3fc013de7b6a9bb1d332c15cfa1796943a2/Frame-44.png" data-mid="72793602" border="0" src="https://freight.cargo.site/w/1000/i/651e52a607cb5607c6c66b1ae409e3fc013de7b6a9bb1d332c15cfa1796943a2/Frame-44.png" /> AR.js studio is an open-source AR platform for creating augmented web experiences. You can create location-based or marker-based AR applications and deploy them straight to web - no coding required! People can create marker-based AR content by uploading their own image... <img width="1604" height="1080" width_o="1604" height_o="1080" data-src="https://freight.cargo.site/t/original/i/ff9c941e05c149110d08108d7eac43284b43a6607e3ed10e026c4992afb7b157/Marker-based-screen.png" data-mid="72807588" border="0" src="https://freight.cargo.site/w/1000/i/ff9c941e05c149110d08108d7eac43284b43a6607e3ed10e026c4992afb7b157/Marker-based-screen.png" /> <img width="1228" height="1486" width_o="1228" height_o="1486" data-src="https://freight.cargo.site/t/original/i/3c87640ca20b7825510ae7d55fff573793d43a612cdf45a5ef9e19d03e52146f/location-based-screen.png" data-mid="72807587" border="0" src="https://freight.cargo.site/w/1000/i/3c87640ca20b7825510ae7d55fff573793d43a612cdf45a5ef9e19d03e52146f/location-based-screen.png" /> ...or location-based content anchored to specific places using GPS coordinates. We were responsible for refining the product flow and creating production-ready UI assets for the MVP, as well as copywriting. The process was truly collaborative; from the start, our working Figma file was openly shared with the whole team to ease communication, inspire feedback and conversation, and maintain transparency througout the process. We also created an openly available communication assets package to establish the visual identity of AR.js Studio. The idea behind this is encourage the practice of open-source design. To make it easy for anyone to remix, improve, and share back their own ideas so we can collectively develop the product. <img width="562" height="338" width_o="562" height_o="338" data-src="https://freight.cargo.site/t/original/i/8de47baa877defe495719fc2f5d8cdac37921411f8ea2742682233e70d2a78f4/commscroll_white.gif" data-mid="72832490" border="0" data-scale="100" src="https://freight.cargo.site/w/562/i/8de47baa877defe495719fc2f5d8cdac37921411f8ea2742682233e70d2a78f4/commscroll_white.gif" /> <img width="2000" height="4114" width_o="2000" height_o="4114" data-src="https://freight.cargo.site/t/original/i/521f743041758499092fd472b5b7a4b9cd0ff08c01678969b55c6da72b74dc27/Ar.js-studio---Components.png" data-mid="72788076" border="0" data-scale="100" src="https://freight.cargo.site/w/1000/i/521f743041758499092fd472b5b7a4b9cd0ff08c01678969b55c6da72b74dc27/Ar.js-studio---Components.png" /> MVP coming soon! Check out our Figma in the meantime. View the full communications package here Here are some recent reflections on the project. https://smeragliuolo.io/Edible-Internet-a-location-tracking-vitamin Wed, 02 Oct 2019 02:26:38 +0000 Anna Smeragliuolo https://smeragliuolo.io/Edible-Internet-a-location-tracking-vitamin a location-tracking vitamin:Edible Internet Location-tracking dietary supplements for a post-privacy futureswallowed by Mantas Lilis, Yuxi Liu, and Anna Smeragliuolo <img width="4942" height="3295" width_o="4942" height_o="3295" data-src="https://freight.cargo.site/t/original/i/dac146403c67809b6f28f71c6d6a26e7e3034881c11eb008dff6d35c86967653/three3.jpg" data-mid="51894810" border="0" src="https://freight.cargo.site/w/1000/i/dac146403c67809b6f28f71c6d6a26e7e3034881c11eb008dff6d35c86967653/three3.jpg" /> Edible Internet is an experience meant to simulate a future where hardware is edible and nothing is secret. The pills are a means of training to prepare people for a world where everyone knows where you are at all times. <img width="3484" height="959" width_o="3484" height_o="959" data-src="https://freight.cargo.site/t/original/i/db2a296a3e8fef8abd638cb37c69f5093559cc17a8dc75797368facee6b994e8/diagram.jpeg" data-mid="51894380" border="0" src="https://freight.cargo.site/w/1000/i/db2a296a3e8fef8abd638cb37c69f5093559cc17a8dc75797368facee6b994e8/diagram.jpeg" /> The experience:&nbsp;Once the pills have been swallowed and your location has been shared, you gain access to a map where you can see the location of everyone else who has swallowed the pills. By frequently sharing their locations, people start to become comfortable with the idea of being perpetually tracked. The project debuted at Ars Electronica 2019. For the event, we created a WhatsApp group to share locations. By using a messaging platform, we observed the added bonus of communication within the group.&nbsp;<img width="600" height="600" width_o="600" height_o="600" data-src="https://freight.cargo.site/t/original/i/2160c6aaa0f8b874170de2b3d840414d2258f6956553376bbcb7f62b675a3da2/map.png" data-mid="51895216" border="0" src="https://freight.cargo.site/w/600/i/2160c6aaa0f8b874170de2b3d840414d2258f6956553376bbcb7f62b675a3da2/map.png" /><img width="1156" height="800" width_o="1156" height_o="800" data-src="https://freight.cargo.site/t/original/i/895a71748080ee3385867063393a1cddabaa753e4d885d72f10b01b276cbc923/chat.png" data-mid="51895217" border="0" src="https://freight.cargo.site/w/1000/i/895a71748080ee3385867063393a1cddabaa753e4d885d72f10b01b276cbc923/chat.png" /> swallow your fears and join the experiment&nbsp;here read some more here https://smeragliuolo.io/Interreality-101-a-VR-concept Wed, 30 Jan 2019 19:26:45 +0000 Anna Smeragliuolo https://smeragliuolo.io/Interreality-101-a-VR-concept a VR concept: Interreality 101 A research project exploring interactions at the intersection of virtual and conventional realityrealized by Anna Smeragliuolo <img width="4129" height="2314" width_o="4129" height_o="2314" data-src="https://freight.cargo.site/t/original/i/bcf9be79aeef2f692fb9ce9479bafbe73bee609bac9afcafa82ab7dc0f729af6/fedeFah_crop.png" data-mid="36829228" border="0" src="https://freight.cargo.site/w/1000/i/bcf9be79aeef2f692fb9ce9479bafbe73bee609bac9afcafa82ab7dc0f729af6/fedeFah_crop.png" /> Virtual reality (VR) and conventional reality (CR) are often positioned as being at odds with each other. Using a VR headset creates an immersive but also isolating experience. You lose connection to those sharing your physical space, and even conversation with CR parties becomes difficult to hear or address. As the industry continues to speculate about the potential of VR, its CR surroundings (people included) are typically ignored. Interreality 101 is a project that starts to define the space where these two realities overlap. where it began: <img width="600" height="338" width_o="600" height_o="338" data-src="https://freight.cargo.site/t/original/i/020a784ad254a1fb035d92987a1c54358c79b185dc59d4d33db0e35661191189/misalignedAxelV.gif" data-mid="36927935" border="0" data-scale="100" src="https://freight.cargo.site/w/600/i/020a784ad254a1fb035d92987a1c54358c79b185dc59d4d33db0e35661191189/misalignedAxelV.gif" /> Interreality was inspired by social VR platforms. These platforms are designed for remote communication. Using VR in a traditionally social scenario (i.e. with friends in physical proximity), is one that has surprisingly been overlooked. I wanted to explore what that scenario might look like. how it became:To investigate these interactions, I conducted a co-creative workshop and ran a series of different experiments to see how we could engage both VR and CR parties in a single shared experience. Each one revealed assumptions I did not know I had, which I was able to use to guide the direction of each new iteration.&nbsp; what it begot: Five principles for designing interactions between virtual worlds and coventional company 1. Be physical - Figure out ways to engage your whole body. Think about bodies in terms of input and feedback, and how they can reveal information about the reality you aren’t in. <img width="600" height="338" width_o="600" height_o="338" data-src="https://freight.cargo.site/t/original/i/a8b8c1da988fcffb2685bdd0a04927c8e79fee8e24ab7b15edbbdcbf997fd718/jinggrab.gif" data-mid="36926115" border="0" src="https://freight.cargo.site/w/600/i/a8b8c1da988fcffb2685bdd0a04927c8e79fee8e24ab7b15edbbdcbf997fd718/jinggrab.gif" /> &nbsp; <img width="600" height="338" width_o="600" height_o="338" data-src="https://freight.cargo.site/t/original/i/5225c08544c33cf861a0655ef439b3374dfaf99f7931d89ea9aab0930e6e9575/woohoo.gif" data-mid="36926179" border="0" src="https://freight.cargo.site/w/600/i/5225c08544c33cf861a0655ef439b3374dfaf99f7931d89ea9aab0930e6e9575/woohoo.gif" /> 2. It feels good to work together - It is especially important to consider when changing VR from an individual to a group experience. Collaborating is a good way to keep both parties engaged. 3. Create imbalances - Give each party access to different information. Think about the things you can’t see while wearing a headset, as well as what you can. This encourages communication between realities. <img width="600" height="338" width_o="600" height_o="338" data-src="https://freight.cargo.site/t/original/i/a5a63a49db7be3637f3c78fe5916c863b82c327b60f17894f87030dfed7f64be/123Strike_small.gif" data-mid="36927847" border="0" src="https://freight.cargo.site/w/600/i/a5a63a49db7be3637f3c78fe5916c863b82c327b60f17894f87030dfed7f64be/123Strike_small.gif" /> <img width="600" height="338" width_o="600" height_o="338" data-src="https://freight.cargo.site/t/original/i/7f4f2dc6bbc3edf63d29287fa745dbbe25a288cab6b6d5976aae40d1a2f164ac/throwing.gif" data-mid="36926364" border="0" src="https://freight.cargo.site/w/600/i/7f4f2dc6bbc3edf63d29287fa745dbbe25a288cab6b6d5976aae40d1a2f164ac/throwing.gif" /> 4. Adjust controls - Explore ways to use the hardware “wrong.” This can be as simple as dividing the controls across parties. Taking away or inverting controls can deepen an interreality experience by creating imbalances for participants to reconcile. 5. Consider space - Virtual space needs conventional space to exist. Instead of eliminating the actual space around you in favor of a simulation, try to use it to your advantage. Shared spatial understanding helps people interact across realities. <img width="1024" height="768" width_o="1024" height_o="768" data-src="https://freight.cargo.site/t/original/i/4dd856687f98d9c676d6399df57049e97a352ec02bbfebd5dc2cdffbaba2316d/joshLooks.gif" data-mid="34194294" border="0" src="https://freight.cargo.site/w/1000/i/4dd856687f98d9c676d6399df57049e97a352ec02bbfebd5dc2cdffbaba2316d/joshLooks.gif" /> more, reiterated more still https://smeragliuolo.io/Learning-Machine-Learning-a-game-of-AI-charades Wed, 30 Jan 2019 19:26:46 +0000 Anna Smeragliuolo https://smeragliuolo.io/Learning-Machine-Learning-a-game-of-AI-charades a game of AI charades: Learning Machine Learning A game of charades based on machine error. played by Anna Smeragliuolo and Mantas Lilis <img width="600" height="375" width_o="600" height_o="375" data-src="https://freight.cargo.site/t/original/i/a6931737cf3bdbd5eb8d96cb703014289b14936d5fbc2355f0273f33635bd455/LML-actionb.gif" data-mid="37172333" border="0" src="https://freight.cargo.site/w/600/i/a6931737cf3bdbd5eb8d96cb703014289b14936d5fbc2355f0273f33635bd455/LML-actionb.gif" /> This is a project about computer perception.About understanding that machines do not operate without error, and in order for them to bend to our wills, we must also bend a little bit to theirs.&nbsp; The game is based on an algorithm called im2txt. It is able to analyze pieces of video, and generate live captions describing what is going on in the scene. here’s the game: The machine generates the caption for a player to act it out. <img width="800" height="800" src="https://freight.cargo.site/w/800/q/67/i/159e7e8b1b1fc63a5de72193e71b4ab4a5065d3eecc7febcf18d2cf23fc2e272/LML-caption.png" style="width: 239.405px; height: 239.405px;"><img width="800" height="800" src="https://freight.cargo.site/w/800/q/67/i/026b8fb678954f36e6e2945687d1373e58681f1a536976ebedb479c5a917daf2/LML-caption-banana.png" style="width: 239.405px; height: 239.405px;">The player tries to act out the caption in front of the camera.After a success, the machine will generate a new caption.<img width="800" height="800" src="https://freight.cargo.site/w/800/q/67/i/128a0b75e6c68d4642101c45753ffc26c295e71a2a5c86d4ae87e0a4109752fb/LML-caption-reset.png" style="width: 239.405px; height: 239.405px;"> here’s the process:To test the limits of im2txt, we took a computer for a walk outside to see how it would perform. We noticed some curious errors and misidentifications. What was it about input that caused it to mislabel the scene? <img width="600" height="359" width_o="600" height_o="359" data-src="https://freight.cargo.site/t/original/i/0e9770aa8f99e06279262631836df0760751e57af0ed293392290596ebfb104a/LNL-Caption-Drinks.gif" data-mid="37092830" border="0" data-scale="100" src="https://freight.cargo.site/w/600/i/0e9770aa8f99e06279262631836df0760751e57af0ed293392290596ebfb104a/LNL-Caption-Drinks.gif" />We tried to trick the algorithm into repeating its own misidentifications, and we realized it felt like playing a game of charades. Sometimes the errors made sense according to human perception - legs as scissors, thick paint as cake, stripes as zebras - other times not so much. &nbsp; <img width="474" height="474" width_o="474" height_o="474" data-src="https://freight.cargo.site/t/original/i/1cae12a28417b739c560be9cc7cb0b3554fae81cea17c9d395e63c2d78434120/almost.png" data-mid="34202320" border="0" data-scale="53" src="https://freight.cargo.site/w/474/i/1cae12a28417b739c560be9cc7cb0b3554fae81cea17c9d395e63c2d78434120/almost.png" /><img width="1200" height="750" width_o="1200" height_o="750" data-src="https://freight.cargo.site/t/original/i/3d7db1855367cc18c6615a947f7652d51b0318b5c25d49305a5743e4eb4a2b0d/bwPhoto.gif" data-mid="37073590" border="0" data-scale="100" src="https://freight.cargo.site/w/1000/i/3d7db1855367cc18c6615a947f7652d51b0318b5c25d49305a5743e4eb4a2b0d/bwPhoto.gif" /> here’s the kicker: As we perform to make the computer understand, we bend to its will -- trying to adjust our behavior to translate its perception into something we can understand. In trying to replicate its point of view, we are no longer teaching the machine; the machine has begun to teach us. https://smeragliuolo.io/Validation-of-the-Leap-Motion-Controller-using-markered-motion Thu, 18 Apr 2019 01:44:26 +0000 Anna Smeragliuolo https://smeragliuolo.io/Validation-of-the-Leap-Motion-Controller-using-markered-motion a paper: Validation of the Leap Motion Controller using markered motion capture technology or how well a Leap Motion can see your hand by Anna Smeragliuolo, N.Jeremy Hill, Luis Disla, and David Putrinoread it here <img width="2135" height="1058" width_o="2135" height_o="1058" data-src="https://freight.cargo.site/t/original/i/6047840d7e42599858654cf5de92c51567d12c0c13e79cb9317e7f2236dc5e80/fig1.png" data-mid="40693333" border="0" alt="Fig. 1. Upper limb anatomical landmarks for marker placement. 1, 2) the acromion processes; 3) center of the sternum; 4) lateral, and 5) medial humeral epicondyles; 6) ulnar, and 7) radial styloid processes; 8) the dorsal side of the wrist centered between the styloid processes; 9) center of the third metacarpal (back of the hand); 10) the middle of the first metacarpal; 11) the distal phalange of the thumb; 12) the distal phalange of the third (middle) finger." data-caption="Fig. 1. Upper limb anatomical landmarks for marker placement. 1, 2) the acromion processes; 3) center of the sternum; 4) lateral, and 5) medial humeral epicondyles; 6) ulnar, and 7) radial styloid processes; 8) the dorsal side of the wrist centered between the styloid processes; 9) center of the third metacarpal (back of the hand); 10) the middle of the first metacarpal; 11) the distal phalange of the thumb; 12) the distal phalange of the third (middle) finger." src="https://freight.cargo.site/w/1000/i/6047840d7e42599858654cf5de92c51567d12c0c13e79cb9317e7f2236dc5e80/fig1.png" /> <img width="1779" height="1381" width_o="1779" height_o="1381" data-src="https://freight.cargo.site/t/original/i/f6afeb86bfc833b34dc529ae354f3f0ce30618eec30016504c26dd57df304a53/fig2.png" data-mid="40693334" border="0" alt="Fig. 2. (Leap Motion Inc.). Typical use: a user controls virtual hands with the Leap Motion." data-caption="Fig. 2. (Leap Motion Inc.). Typical use: a user controls virtual hands with the Leap Motion." src="https://freight.cargo.site/w/1000/i/f6afeb86bfc833b34dc529ae354f3f0ce30618eec30016504c26dd57df304a53/fig2.png" /> <img width="2534" height="1222" width_o="2534" height_o="1222" data-src="https://freight.cargo.site/t/original/i/4f915fefdf4fdf161afb5d64723ec487e64af26fcfb4b11877bf2e8c957791e0/fig4.png" data-mid="40693336" border="0" data-scale="100" alt="Fig. 4. Hand movements: a) radial/ulnar deviation, b) flexion/extension, and c) supination/pronation. Hand positions: d) open hand, e) loose fist, and f) tight fist." data-caption="Fig. 4. Hand movements: a) radial/ulnar deviation, b) flexion/extension, and c) supination/pronation. Hand positions: d) open hand, e) loose fist, and f) tight fist." src="https://freight.cargo.site/w/1000/i/4f915fefdf4fdf161afb5d64723ec487e64af26fcfb4b11877bf2e8c957791e0/fig4.png" /> <img width="2178" height="1058" width_o="2178" height_o="1058" data-src="https://freight.cargo.site/t/original/i/4e67c59351c18061aabfe34fa468e6f9adb56fc9d54b82955f582260c9651d6d/fig5.png" data-mid="40693337" border="0" alt="Fig. 5. Neutral positions of the wrist and corresponding axes. a) ISB recommended neutral wrist position, with grey arrows describing our rotational adjustments. b) Adjusted neutral wrist position for Leap Motion." data-caption="Fig. 5. Neutral positions of the wrist and corresponding axes. a) ISB recommended neutral wrist position, with grey arrows describing our rotational adjustments. b) Adjusted neutral wrist position for Leap Motion." src="https://freight.cargo.site/w/1000/i/4e67c59351c18061aabfe34fa468e6f9adb56fc9d54b82955f582260c9651d6d/fig5.png" /> <img width="1612" height="2054" width_o="1612" height_o="2054" data-src="https://freight.cargo.site/t/original/i/d05d1e4c988599af9c01541644ae8c414823a7647fd97ef9e4b4375fd01f5e27/fig6.png" data-mid="40693338" border="0" data-scale="90" alt="Fig. 6. a) Flexion/extension Bias across range. Negative x-values represent flexion for both right and left hands; positive x-values represent extension for both hands. Mean bias 72 standard deviations are delineated on the plot to highlight differing accuracy levels. b) Flexion/extension RMSE across range: Negative x-values represent flexion for both right and left hands; positive x-values represent extension for both hands. Data points attributed to the right hand are represented by warm colors, the left hand by cool colors. Effective ranges are shaded. The hands represented on the negative and positive sides of the x-axis indicate the directions of movement for both the right and left hands. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)" data-caption="Fig. 6. a) Flexion/extension Bias across range. Negative x-values represent flexion for both right and left hands; positive x-values represent extension for both hands. Mean bias 72 standard deviations are delineated on the plot to highlight differing accuracy levels. b) Flexion/extension RMSE across range: Negative x-values represent flexion for both right and left hands; positive x-values represent extension for both hands. Data points attributed to the right hand are represented by warm colors, the left hand by cool colors. Effective ranges are shaded. The hands represented on the negative and positive sides of the x-axis indicate the directions of movement for both the right and left hands. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)" src="https://freight.cargo.site/w/1000/i/d05d1e4c988599af9c01541644ae8c414823a7647fd97ef9e4b4375fd01f5e27/fig6.png" /> <img width="1812" height="2036" width_o="1812" height_o="2036" data-src="https://freight.cargo.site/t/original/i/f1fe19ab15af585e11e2f169d1f00867cbf5f8b9d4c1d82614fb79a34bb46845/fig7.png" data-mid="40693339" border="0" alt="Fig. 7. a) Radial/ulnar deviation Bias magnitude across range: Negative x-values represent radial deviation of the right hand and ulnar deviation of the left hand; positive x- values represent ulnar deviation of the right hand and radial deviation of the left. Mean Bias 72 standard deviations are delineated on the plot to highlight differing accuracy levels. b) Radial/ulnar deviation RMSE across range: Negative x-values represent radial deviation of the right hand and ulnar deviation of the left hand; positive x- values represent ulnar deviation of the right hand and radial deviation of the left. Data points attributed to the right hand are represented by warm colors, the left hand by cool colors. Effective ranges are shaded. The hands represented on the negative and positive sides of the x-axis indicate the directions of movement for both the right and left hands. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)" data-caption="Fig. 7. a) Radial/ulnar deviation Bias magnitude across range: Negative x-values represent radial deviation of the right hand and ulnar deviation of the left hand; positive x- values represent ulnar deviation of the right hand and radial deviation of the left. Mean Bias 72 standard deviations are delineated on the plot to highlight differing accuracy levels. b) Radial/ulnar deviation RMSE across range: Negative x-values represent radial deviation of the right hand and ulnar deviation of the left hand; positive x- values represent ulnar deviation of the right hand and radial deviation of the left. Data points attributed to the right hand are represented by warm colors, the left hand by cool colors. Effective ranges are shaded. The hands represented on the negative and positive sides of the x-axis indicate the directions of movement for both the right and left hands. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)" src="https://freight.cargo.site/w/1000/i/f1fe19ab15af585e11e2f169d1f00867cbf5f8b9d4c1d82614fb79a34bb46845/fig7.png" /> <img width="1908" height="2056" width_o="1908" height_o="2056" data-src="https://freight.cargo.site/t/original/i/2ec4a56123b5acb02d8fe8d15290f94c27f556e0c57eed9c5761e9c65934b2a1/fig8.png" data-mid="40693340" border="0" alt="Fig. 8. a) Pronation/supination Bias magnitude across range: Negative x-values represent supination of the right hand and pronation of the left hand; positive x-values represent pronation of the right hand and supination of the left. Mean Bias 72 standard deviations are delineated on the plot to highlight differing accuracy levels. b) Supination/pronation RMSE across range: Negative x-values represent supination of the right hand and pronation of the left hand; positive x-values represent pronation of the right hand and supination of the left. Data points attributed to the right hand are represented by warm colors, the left hand by cool colors. No effective range was identified for this movement. The hands represented on the negative and positive sides of the x-axis indicate the directions of movement for both the right and left hands. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)" data-caption="Fig. 8. a) Pronation/supination Bias magnitude across range: Negative x-values represent supination of the right hand and pronation of the left hand; positive x-values represent pronation of the right hand and supination of the left. Mean Bias 72 standard deviations are delineated on the plot to highlight differing accuracy levels. b) Supination/pronation RMSE across range: Negative x-values represent supination of the right hand and pronation of the left hand; positive x-values represent pronation of the right hand and supination of the left. Data points attributed to the right hand are represented by warm colors, the left hand by cool colors. No effective range was identified for this movement. The hands represented on the negative and positive sides of the x-axis indicate the directions of movement for both the right and left hands. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)" src="https://freight.cargo.site/w/1000/i/2ec4a56123b5acb02d8fe8d15290f94c27f556e0c57eed9c5761e9c65934b2a1/fig8.png" /> https://smeragliuolo.io/Using-data-from-the-Microsoft-Kinect-2-to-determine-postural Thu, 18 Apr 2019 01:13:03 +0000 Anna Smeragliuolo https://smeragliuolo.io/Using-data-from-the-Microsoft-Kinect-2-to-determine-postural another paper: Using data from the Microsoft Kinect 2 to determine postural stability in healthy subjects: A feasibility trial or machine learning is how a Kinect can tell what you are doing better than a fancy force plate can by Behdad Dehbandi, Alexandre Barachant, Anna Smeragliuolo, John Davis Long, Silverio Joseph Bumanlag, Victor He, Anna Lampe, and David Putrino read it here <img width="2088" height="1352" width_o="2088" height_o="1352" data-src="https://freight.cargo.site/t/original/i/c31ed43146ff056b0012d57a8363aa9c0266803d72f66ec3705b6d6dd6653b81/setup.png" data-mid="40299976" border="0" alt="Fig 1. Experimental layout for data collection: subjects sat on a rectangular box that was placed in the center of the KFP at a distance of 2.7 meters from the MK2. The MK2 was mounted on a tripod 0.92 meters from the floor." data-caption="Fig 1. Experimental layout for data collection: subjects sat on a rectangular box that was placed in the center of the KFP at a distance of 2.7 meters from the MK2. The MK2 was mounted on a tripod 0.92 meters from the floor." src="https://freight.cargo.site/w/1000/i/c31ed43146ff056b0012d57a8363aa9c0266803d72f66ec3705b6d6dd6653b81/setup.png" /> <img width="2296" height="1264" width_o="2296" height_o="1264" data-src="https://freight.cargo.site/t/original/i/bb708ee1b4903e053269ba7ebd036f7b21be5dfa9167c6c55847aedb6a68f904/seatedPoses.png" data-mid="40299977" border="0" data-scale="100" alt="Fig 2. Three postural conditions. a) Both feet on the ground. b) One foot off the ground. c) Both feet off the ground." data-caption="Fig 2. Three postural conditions. a) Both feet on the ground. b) One foot off the ground. c) Both feet off the ground." src="https://freight.cargo.site/w/1000/i/bb708ee1b4903e053269ba7ebd036f7b21be5dfa9167c6c55847aedb6a68f904/seatedPoses.png" /> <img width="1744" height="1224" width_o="1744" height_o="1224" data-src="https://freight.cargo.site/t/original/i/16c12dfa176b28f5163a187ad77867ffc0e98a44e897e299f1b3f8d72998c183/clusters.png" data-mid="40299978" border="0" alt="Fig 6. t-SNE representation of the dataset for the MK2 (left) and the KFP (right). A clear separation between tasks can be observed for both devices, but the MK2 data are more separable. Each cluster is formed by the points of the 3 conditions performed under the corresponding task. A zoom over the cluster of task 5 highlights a lower separation of the conditions." data-caption="Fig 6. t-SNE representation of the dataset for the MK2 (left) and the KFP (right). A clear separation between tasks can be observed for both devices, but the MK2 data are more separable. Each cluster is formed by the points of the 3 conditions performed under the corresponding task. A zoom over the cluster of task 5 highlights a lower separation of the conditions." src="https://freight.cargo.site/w/1000/i/16c12dfa176b28f5163a187ad77867ffc0e98a44e897e299f1b3f8d72998c183/clusters.png" /> https://smeragliuolo.io/Leap-Motion-a-poster Thu, 18 Apr 2019 03:57:57 +0000 Anna Smeragliuolo https://smeragliuolo.io/Leap-Motion-a-poster a poster:Validation of the Leap Motion’s Hand Recognition Capabilities and Limitations poster presentation for Burke Medical Research Institute summer scholars poster day by Anna Smeragliuolo, Divija Chopra, Matthew Marano, Luis Disla, and David Putrino <img width="3600" height="4800" width_o="3600" height_o="4800" data-src="https://freight.cargo.site/t/original/i/f9d30bbe376a752fe1ac98a3878f4af072f08ec3457dbd9d3ba82f6b12183c0f/MoCap-Poster-final4_3600.png" data-mid="40306269" border="0" src="https://freight.cargo.site/w/1000/i/f9d30bbe376a752fe1ac98a3878f4af072f08ec3457dbd9d3ba82f6b12183c0f/MoCap-Poster-final4_3600.png" /> https://smeragliuolo.io/Use-a-Touch-Sensor-to-Make-an-Interactive-Box-of-Live-Spiders-a-box Thu, 07 Mar 2019 18:42:39 +0000 Anna Smeragliuolo https://smeragliuolo.io/Use-a-Touch-Sensor-to-Make-an-Interactive-Box-of-Live-Spiders-a-box a box of AR spiders: Use a Touch Sensor to Make an Interactive Box of Live Spiders! a tutorial on how to make your friends squeal in disgust as they physically touch digital spiders touched by Anna Smeragliuolo and Reuben DSilva&nbsp; <img width="600" height="338" width_o="600" height_o="338" data-src="https://freight.cargo.site/t/original/i/48d60a0a579eed1739341b6c6ce65fe5b8d4a4ab91da871e75182b0c235b39a1/demo.gif" data-mid="37089705" border="0" src="https://freight.cargo.site/w/600/i/48d60a0a579eed1739341b6c6ce65fe5b8d4a4ab91da871e75182b0c235b39a1/demo.gif" /> tutorial&nbsp;