{"id":{"repo_id":"carleton","oai_identifier":"oai:carleton.scholaris.ca:20.500.14718/41558"},"canonical_url":"https://search.dev.ndltd.org/etd/carleton/oai:carleton.scholaris.ca:20.500.14718/41558","repository":{"repo_id":"carleton","name":"Carleton University","base_url":"https://carleton.scholaris.ca/server/oai/request"},"display":{"title":"Automatic Page-Turner for Pianists With Wearable Motion Detector","abstract":"Turning book pages is a simple act that readers do while reading. This simple act that we take for granted could be challenging when both hands are engaged in other tasks. In case that a pianist sight-read, using one hand for turning the music sheets can cause distraction or short delay in their performance. Previous studies predominantly utilized audio or video processing techniques for following the musicians' performance. We suggested a framework that uses wearable technologies as an alternative solution for solving page-turning problems. The proposed design recognizes the pianist's wrists oscillatory motion with accelerometer sensors and tries to sync them to digital music notes. This system uses dynamic time warping and cross-correlation methods to find the optimum alignment between actual and captured data and reducing time latency. Eventually, a heuristic decision model assesses the pianist's performance and decides to turn the digital music sheet at predefined points.","abstract_html":"Turning book pages is a simple act that readers do while reading. This simple act that we take for granted could be challenging when both hands are engaged in other tasks. In case that a pianist sight-read, using one hand for turning the music sheets can cause distraction or short delay in their performance. Previous studies predominantly utilized audio or video processing techniques for following the musicians' performance. We suggested a framework that uses wearable technologies as an alternative solution for solving page-turning problems. The proposed design recognizes the pianist's wrists oscillatory motion with accelerometer sensors and tries to sync them to digital music notes. This system uses dynamic time warping and cross-correlation methods to find the optimum alignment between actual and captured data and reducing time latency. Eventually, a heuristic decision model assesses the pianist's performance and decides to turn the digital music sheet at predefined points.","abstract_has_math":false,"creators":["Mirazimzadeh, Seyed Ali"],"institution":"Carleton University","degree_name":"Master of Applied Science (M.App.Sc.)","degree_level":"Master's","degree_discipline":"Human-Computer Interaction","degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2021,"date_issued":"2021","date_published":"2021","updated_at":"2026-07-24T01:34:30Z","subjects":[],"languages":["en"],"rights":["Copyright © 2021 the author(s). Theses may be used for non-commercial research, educational, or related academic purposes only. Such uses include personal study, research, scholarship, and teaching. Theses may only be shared by linking to Carleton University Institutional Repository and no part may be used without proper attribution to the author. 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Theses may be used for non-commercial research, educational, or related academic purposes only. Such uses include personal study, research, scholarship, and teaching. Theses may only be shared by linking to Carleton University Institutional Repository and no part may be used without proper attribution to the author. No part may be used for commercial purposes directly or indirectly via a for-profit platform; no adaptation or derivative works are permitted without consent from the copyright owner."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.doi","label":"DOI","values":["10.22215/etd/2021-14386"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/20.500.14718/41558"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Turning book pages is a simple act that readers do while reading. This simple act that we take for granted could be challenging when both hands are engaged in other tasks. In case that a pianist sight-read, using one hand for turning the music sheets can cause distraction or short delay in their performance. Previous studies predominantly utilized audio or video processing techniques for following the musicians' performance. We suggested a framework that uses wearable technologies as an alternative solution for solving page-turning problems. The proposed design recognizes the pianist's wrists oscillatory motion with accelerometer sensors and tries to sync them to digital music notes. This system uses dynamic time warping and cross-correlation methods to find the optimum alignment between actual and captured data and reducing time latency. Eventually, a heuristic decision model assesses the pianist's performance and decides to turn the digital music sheet at predefined points."]},{"key":"dc:title","label":"Title","values":["Automatic Page-Turner for Pianists With Wearable Motion Detector"]}]}],"canonical_facts":{"dc:creator":["Mirazimzadeh, Seyed Ali"],"dc:date.accessioned":["2025-04-08T20:21:31Z"],"dc:date.available":["2025-04-08T20:21:31Z"],"dc:date.issued":["2021"],"dc:description.abstract":["Turning book pages is a simple act that readers do while reading. This simple act that we take for granted could be challenging when both hands are engaged in other tasks. In case that a pianist sight-read, using one hand for turning the music sheets can cause distraction or short delay in their performance. Previous studies predominantly utilized audio or video processing techniques for following the musicians' performance. We suggested a framework that uses wearable technologies as an alternative solution for solving page-turning problems. The proposed design recognizes the pianist's wrists oscillatory motion with accelerometer sensors and tries to sync them to digital music notes. This system uses dynamic time warping and cross-correlation methods to find the optimum alignment between actual and captured data and reducing time latency. Eventually, a heuristic decision model assesses the pianist's performance and decides to turn the digital music sheet at predefined points."],"dc:identifier.doi":["10.22215/etd/2021-14386"],"dc:identifier.uri":["https://hdl.handle.net/20.500.14718/41558"],"dc:language.iso":["en"],"dc:publisher":["Carleton University"],"dc:rights":["Copyright © 2021 the author(s). Theses may be used for non-commercial research, educational, or related academic purposes only. Such uses include personal study, research, scholarship, and teaching. 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