{"id":{"repo_id":"reykjavik","oai_identifier":"oai:skemman.is:1946/44889"},"canonical_url":"https://search.dev.ndltd.org/etd/reykjavik/oai:skemman.is:1946/44889","repository":{"repo_id":"reykjavik","name":"Reykjavík University","base_url":"https://skemman.is/oai/request"},"display":{"title":"Using virtual reality and kinematic measurements to assess the interplay between motion sickness, neck pain, heart variables and postural control response","abstract":"Motion sickness and neck pain can affect the postural control of individuals. During motion sickness, sensory systems are disrupted and can lead to impaired postural control. However, regarding neck pain, the condition of the cervical muscles can affect how well individuals can maintain balance. The aim of this study is to investigate the relationship between motion sickness, postural control, neck pain, and heart variables during kinematic measurements. Twenty subjects participated in the study and performed two measurements. They also answered questionnaires that were used to determine the classification of the subjects. The first measurement is called BioVRSea; it is used to assess motion sickness and it measures center of pressure, heart variables, and head movement when the subject is immersed in a virtual reality environment in conjunction with a moving platform. The other is called NeckSmart and measures neck proprioception, movement control and range of motion. Statistical analysis and machine learning approaches were used to gain an understanding of the data and categorize subjects based on outcome variables and self-reported questionnaires. Correlations were found between numerous kinematic and physiological variables examined in this study. For example, it was discovered that both neck mobility and heart rate variables are highly correlated with motion sickness. Correlation between neck pain and heart rate as well as postural control was also discovered. This study demonstrates that machine learning is a useful tool for identifying the most important variables to look for when distinguishing between motion sickness and proprioception impairment.","abstract_html":"Motion sickness and neck pain can affect the postural control of individuals. During motion sickness, sensory systems are disrupted and can lead to impaired postural control. However, regarding neck pain, the condition of the cervical muscles can affect how well individuals can maintain balance. The aim of this study is to investigate the relationship between motion sickness, postural control, neck pain, and heart variables during kinematic measurements. Twenty subjects participated in the study and performed two measurements. They also answered questionnaires that were used to determine the classification of the subjects. The first measurement is called BioVRSea; it is used to assess motion sickness and it measures center of pressure, heart variables, and head movement when the subject is immersed in a virtual reality environment in conjunction with a moving platform. The other is called NeckSmart and measures neck proprioception, movement control and range of motion. Statistical analysis and machine learning approaches were used to gain an understanding of the data and categorize subjects based on outcome variables and self-reported questionnaires. Correlations were found between numerous kinematic and physiological variables examined in this study. For example, it was discovered that both neck mobility and heart rate variables are highly correlated with motion sickness. Correlation between neck pain and heart rate as well as postural control was also discovered. This study demonstrates that machine learning is a useful tool for identifying the most important variables to look for when distinguishing between motion sickness and proprioception impairment.","abstract_has_math":false,"creators":["Hekla Bryndís Jóhannsdóttir 1997-"],"institution":null,"degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":["Háskólinn í Reykjavík"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2023,"date_issued":"2023-06-08T13:53:07Z","date_published":"2023-06-08T13:53:07Z","updated_at":"2026-07-27T20:38:22Z","subjects":["Heilbrigðisverkfræði","Meistaraprófsritgerðir","Sýndarveruleiki","Hreyfingar (lífeðlisfræði)","Mælingar","Hreyfiveiki","Hálsvöðvar","Verkir","Hjartsláttartruflanir","Líkamsstaða","Biomedical engineering","Virtual reality in medicine","Kinematics","Interplay","Motion sickness","Neck pain","Arrhythmia","Postural Balance"],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/1946/44889","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Háskólinn í Reykjavík"]},{"key":"dc:creator","label":"Author","values":["Hekla Bryndís Jóhannsdóttir 1997-"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2023-06-08T13:53:05Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2023-06-08T13:53:05Z"]},{"key":"dc:date.issued","label":"Date","values":["2023-06-08T13:53:07Z"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Heilbrigðisverkfræði","Meistaraprófsritgerðir","Sýndarveruleiki","Hreyfingar (lífeðlisfræði)","Mælingar","Hreyfiveiki","Hálsvöðvar","Verkir","Hjartsláttartruflanir","Líkamsstaða","Biomedical engineering","Virtual reality in medicine","Kinematics","Interplay","Motion sickness","Neck pain","Arrhythmia","Postural Balance"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/1946/44889"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Motion sickness and neck pain can affect the postural control of individuals. During motion sickness, sensory systems are disrupted and can lead to impaired postural control. However, regarding neck pain, the condition of the cervical muscles can affect how well individuals can maintain balance. The aim of this study is to investigate the relationship between motion sickness, postural control, neck pain, and heart variables during kinematic measurements. Twenty subjects participated in the study and performed two measurements. They also answered questionnaires that were used to determine the classification of the subjects. The first measurement is called BioVRSea; it is used to assess motion sickness and it measures center of pressure, heart variables, and head movement when the subject is immersed in a virtual reality environment in conjunction with a moving platform. The other is called NeckSmart and measures neck proprioception, movement control and range of motion. Statistical analysis and machine learning approaches were used to gain an understanding of the data and categorize subjects based on outcome variables and self-reported questionnaires. Correlations were found between numerous kinematic and physiological variables examined in this study. For example, it was discovered that both neck mobility and heart rate variables are highly correlated with motion sickness. Correlation between neck pain and heart rate as well as postural control was also discovered. This study demonstrates that machine learning is a useful tool for identifying the most important variables to look for when distinguishing between motion sickness and proprioception impairment."]},{"key":"dc:title","label":"Title","values":["Using virtual reality and kinematic measurements to assess the interplay between motion sickness, neck pain, heart variables and postural control response"]}]}],"canonical_facts":{"dc:contributor":["Háskólinn í Reykjavík"],"dc:creator":["Hekla Bryndís Jóhannsdóttir 1997-"],"dc:date.accessioned":["2023-06-08T13:53:05Z"],"dc:date.available":["2023-06-08T13:53:05Z"],"dc:date.issued":["2023-06-08T13:53:07Z"],"dc:description.abstract":["Motion sickness and neck pain can affect the postural control of individuals. During motion sickness, sensory systems are disrupted and can lead to impaired postural control. However, regarding neck pain, the condition of the cervical muscles can affect how well individuals can maintain balance. The aim of this study is to investigate the relationship between motion sickness, postural control, neck pain, and heart variables during kinematic measurements. Twenty subjects participated in the study and performed two measurements. They also answered questionnaires that were used to determine the classification of the subjects. The first measurement is called BioVRSea; it is used to assess motion sickness and it measures center of pressure, heart variables, and head movement when the subject is immersed in a virtual reality environment in conjunction with a moving platform. The other is called NeckSmart and measures neck proprioception, movement control and range of motion. Statistical analysis and machine learning approaches were used to gain an understanding of the data and categorize subjects based on outcome variables and self-reported questionnaires. Correlations were found between numerous kinematic and physiological variables examined in this study. For example, it was discovered that both neck mobility and heart rate variables are highly correlated with motion sickness. Correlation between neck pain and heart rate as well as postural control was also discovered. This study demonstrates that machine learning is a useful tool for identifying the most important variables to look for when distinguishing between motion sickness and proprioception impairment."],"dc:identifier.uri":["http://hdl.handle.net/1946/44889"],"dc:language.iso":["en"],"dc:subject":["Heilbrigðisverkfræði","Meistaraprófsritgerðir","Sýndarveruleiki","Hreyfingar (lífeðlisfræði)","Mælingar","Hreyfiveiki","Hálsvöðvar","Verkir","Hjartsláttartruflanir","Líkamsstaða","Biomedical engineering","Virtual reality in medicine","Kinematics","Interplay","Motion sickness","Neck pain","Arrhythmia","Postural Balance"],"dc:title":["Using virtual reality and kinematic measurements to assess the interplay between motion sickness, neck pain, heart variables and postural control response"],"dc:type":["Thesis"]},"updated_at":"2026-07-27T20:38:22Z"}