Yannick Francillette, B. Bouchard, Eric Boucher, S. Gaboury, P. Bernard, A. Romain, K. Bouchard
Maintaining a certain level of Physical Activity (PA) is important to prevent some chronic pathologies. This is even more important for individuals with severe mental health problems, but they have many barriers that make it very difficult for them to be physically active, including lack of motivation. In this paper, we propose an exergame that aims to help these people integrate PA into their daily lives. This exergame is designed on a smartphone in order to be able to follow the level of activity of the player on a daily basis. It offers game mechanics that allow the player to manage their PA. However, it encourages them to be physically active so that they can progress more easily in the game. The application uses an activity detection algorithm to measure the level of PA. We offer a preliminary study on healthy subjects on a demo version of the game that observes their gaming experience. The results show that the mechanics are globally appreciated and that the game allows each player to manage his PA as he wishes.
{"title":"Development of an Exergame on Mobile Phones to Increase Physical Activity for Adults with Severe Mental Illness","authors":"Yannick Francillette, B. Bouchard, Eric Boucher, S. Gaboury, P. Bernard, A. Romain, K. Bouchard","doi":"10.1145/3197768.3201521","DOIUrl":"https://doi.org/10.1145/3197768.3201521","url":null,"abstract":"Maintaining a certain level of Physical Activity (PA) is important to prevent some chronic pathologies. This is even more important for individuals with severe mental health problems, but they have many barriers that make it very difficult for them to be physically active, including lack of motivation. In this paper, we propose an exergame that aims to help these people integrate PA into their daily lives. This exergame is designed on a smartphone in order to be able to follow the level of activity of the player on a daily basis. It offers game mechanics that allow the player to manage their PA. However, it encourages them to be physically active so that they can progress more easily in the game. The application uses an activity detection algorithm to measure the level of PA. We offer a preliminary study on healthy subjects on a demo version of the game that observes their gaming experience. The results show that the mechanics are globally appreciated and that the game allows each player to manage his PA as he wishes.","PeriodicalId":130190,"journal":{"name":"Proceedings of the 11th PErvasive Technologies Related to Assistive Environments Conference","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123885006","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In recent years robots have been replacing human workers in many industries. As robot manufacturing becomes more optimized and cost effective, the use of robots is going to evolve in various fields. Thus, it is essential to prepare workers to operate robots and work collaboratively with them side by side. In this paper, we are proposing a human-robot collaborative task to assess human performance in experimental, industrial setup. The task is designed in both virtual and physical environments.
{"title":"A Collaborative Assembly Task to Assess Worker Skills in Robot Manufacturing Environments","authors":"M. Abujelala, Sanika Gupta, F. Makedon","doi":"10.1145/3197768.3203171","DOIUrl":"https://doi.org/10.1145/3197768.3203171","url":null,"abstract":"In recent years robots have been replacing human workers in many industries. As robot manufacturing becomes more optimized and cost effective, the use of robots is going to evolve in various fields. Thus, it is essential to prepare workers to operate robots and work collaboratively with them side by side. In this paper, we are proposing a human-robot collaborative task to assess human performance in experimental, industrial setup. The task is designed in both virtual and physical environments.","PeriodicalId":130190,"journal":{"name":"Proceedings of the 11th PErvasive Technologies Related to Assistive Environments Conference","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124247346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Oliver Korn, R. Holt, Efstratios Kontopoulos, A. Kappers, N. Persson, Nasrine Olson
Deafblindness is a condition that limits communication capabilities primarily to the haptic channel. In the EU-funded project SUITCEYES we design a system which allows haptic and thermal communication via soft interfaces and textiles. Based on user needs and informed by disability studies, we combine elements from smart textiles, sensors, semantic technologies, image processing, face and object recognition, machine learning, affective computing, and gamification. In this work, we present the underlying concepts and the overall design vision of the resulting assistive smart wearable.
{"title":"Empowering Persons with Deafblindness: Designing an Intelligent Assistive Wearable in the SUITCEYES Project","authors":"Oliver Korn, R. Holt, Efstratios Kontopoulos, A. Kappers, N. Persson, Nasrine Olson","doi":"10.1145/3197768.3201541","DOIUrl":"https://doi.org/10.1145/3197768.3201541","url":null,"abstract":"Deafblindness is a condition that limits communication capabilities primarily to the haptic channel. In the EU-funded project SUITCEYES we design a system which allows haptic and thermal communication via soft interfaces and textiles. Based on user needs and informed by disability studies, we combine elements from smart textiles, sensors, semantic technologies, image processing, face and object recognition, machine learning, affective computing, and gamification. In this work, we present the underlying concepts and the overall design vision of the resulting assistive smart wearable.","PeriodicalId":130190,"journal":{"name":"Proceedings of the 11th PErvasive Technologies Related to Assistive Environments Conference","volume":"218 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116468964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. Hollmén, L. Asker, Isak Karlsson, P. Papapetrou, Henrik Boström, B. N. Wikner, Inger Öhman
Electronic health records contain a wealth of epidemiological information about diseases at the population level. Using a database of medical diagnoses and drug prescriptions in electronic health records, we investigate the correlation between outdoor temperature and the incidence of epistaxis over time for two groups of patients. One group consists of patients that had been diagnosed with epistaxis and also been prescribed at least one of the three anti-thrombotic agents: Warfarin, Apixaban, or Rivaroxaban. The other group consists of patients that had been diagnosed with epistaxis and not been prescribed any of the three anti-thrombotic drugs. We find a strong negative correlation between the incidence of epistaxis and outdoor temperature for the group that had not been prescribed any of the three anti-thrombotic drugs, while there is a weaker correlation between incidence of epistaxis and outdoor temperature for the other group. It is, however, clear that both groups are affected in a similar way, such that the incidence of epistaxis increases with colder temperatures.
{"title":"Exploring epistaxis as an adverse effect of anti-thrombotic drugs and outdoor temperature","authors":"J. Hollmén, L. Asker, Isak Karlsson, P. Papapetrou, Henrik Boström, B. N. Wikner, Inger Öhman","doi":"10.1145/3197768.3197769","DOIUrl":"https://doi.org/10.1145/3197768.3197769","url":null,"abstract":"Electronic health records contain a wealth of epidemiological information about diseases at the population level. Using a database of medical diagnoses and drug prescriptions in electronic health records, we investigate the correlation between outdoor temperature and the incidence of epistaxis over time for two groups of patients. One group consists of patients that had been diagnosed with epistaxis and also been prescribed at least one of the three anti-thrombotic agents: Warfarin, Apixaban, or Rivaroxaban. The other group consists of patients that had been diagnosed with epistaxis and not been prescribed any of the three anti-thrombotic drugs. We find a strong negative correlation between the incidence of epistaxis and outdoor temperature for the group that had not been prescribed any of the three anti-thrombotic drugs, while there is a weaker correlation between incidence of epistaxis and outdoor temperature for the other group. It is, however, clear that both groups are affected in a similar way, such that the incidence of epistaxis increases with colder temperatures.","PeriodicalId":130190,"journal":{"name":"Proceedings of the 11th PErvasive Technologies Related to Assistive Environments Conference","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123250297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Haseeb, Maria Kyrarini, Shuo Jiang, Danijela Ristić-Durrant, A. Gräser
Development of assistive robotics to enable people with disabilities to work is a challenging topic. Hands-free interfaces can support a person with severe motor impairments to control robotic manipulators. The paper focuses on developing a head gesture interface, which enables the end-user to control a dual-arm industrial robot. A motion sensor is located on the head of the end-user. Support vector machine is used to recognize the head gestures and an intuitive Graphical User Interface is developed to help the user to navigate through different control modes. To evaluate the proposed framework, an industrial pick and place task was performed.
{"title":"Head Gesture-based Control for Assistive Robots","authors":"M. Haseeb, Maria Kyrarini, Shuo Jiang, Danijela Ristić-Durrant, A. Gräser","doi":"10.1145/3197768.3201574","DOIUrl":"https://doi.org/10.1145/3197768.3201574","url":null,"abstract":"Development of assistive robotics to enable people with disabilities to work is a challenging topic. Hands-free interfaces can support a person with severe motor impairments to control robotic manipulators. The paper focuses on developing a head gesture interface, which enables the end-user to control a dual-arm industrial robot. A motion sensor is located on the head of the end-user. Support vector machine is used to recognize the head gestures and an intuitive Graphical User Interface is developed to help the user to navigate through different control modes. To evaluate the proposed framework, an industrial pick and place task was performed.","PeriodicalId":130190,"journal":{"name":"Proceedings of the 11th PErvasive Technologies Related to Assistive Environments Conference","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123458261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In real-time gesture recognition algorithms, accurately classifying gestures early, when they are only partially observed, can be advantageous as it minimizes latency and improves user experience. This work investigates a novel approach for improving the results of an early gesture classification model. The method involves augmenting the input sequence of human poses of a partially observed gesture with a series of poses predicted by an auxiliary recurrent neural network sequence-to-sequence motion prediction model before being fed into a random forest gesture classifier. By concatenating the partially observed ground truth sequence with the forecasted motion sequence, we are able to significantly improve early gesture recognition accuracy. When forecasting 25 future frames of a partially observed input gesture sequence of 50 frames, recognition accuracy improves from 45% to 87% on average when evaluated on the MSRC-12 gesture dataset.
{"title":"Enabling Early Gesture Recognition by Motion Augmentation","authors":"R. Agrawal, Ajjen Joshi, Margrit Betke","doi":"10.1145/3197768.3197788","DOIUrl":"https://doi.org/10.1145/3197768.3197788","url":null,"abstract":"In real-time gesture recognition algorithms, accurately classifying gestures early, when they are only partially observed, can be advantageous as it minimizes latency and improves user experience. This work investigates a novel approach for improving the results of an early gesture classification model. The method involves augmenting the input sequence of human poses of a partially observed gesture with a series of poses predicted by an auxiliary recurrent neural network sequence-to-sequence motion prediction model before being fed into a random forest gesture classifier. By concatenating the partially observed ground truth sequence with the forecasted motion sequence, we are able to significantly improve early gesture recognition accuracy. When forecasting 25 future frames of a partially observed input gesture sequence of 50 frames, recognition accuracy improves from 45% to 87% on average when evaluated on the MSRC-12 gesture dataset.","PeriodicalId":130190,"journal":{"name":"Proceedings of the 11th PErvasive Technologies Related to Assistive Environments Conference","volume":"133 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114853760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Social companion robots are intentionally developed and designed to support humans in useful tasks and to use social cues to establish a relationship to the user. However, so far no social companion robots existed outside of research labs to perform long-term studies "in the wild", exploring how this relationship actually evolves over time. In this paper we present the research agenda for such a study using the soon commercially available BUDDY robot from Blue Frog Robotics. We chose a sociological ethnographic approach with eight households, methodologically mainly focusing on qualitative data gathered through a series of household visits. For data analysis we aim at extending the Domestic Robot Ecology (DRE), which was originally developed based on ethnographic studies with vacuum cleaning robots, and for data interpretation we base our work on a newly proposed sociological framework, we call everyday-life centered approach (ELCA).
{"title":"What makes people accept or reject companion robots?: A research agenda","authors":"A. Weiss, Glenda Hannibal","doi":"10.1145/3197768.3203177","DOIUrl":"https://doi.org/10.1145/3197768.3203177","url":null,"abstract":"Social companion robots are intentionally developed and designed to support humans in useful tasks and to use social cues to establish a relationship to the user. However, so far no social companion robots existed outside of research labs to perform long-term studies \"in the wild\", exploring how this relationship actually evolves over time. In this paper we present the research agenda for such a study using the soon commercially available BUDDY robot from Blue Frog Robotics. We chose a sociological ethnographic approach with eight households, methodologically mainly focusing on qualitative data gathered through a series of household visits. For data analysis we aim at extending the Domestic Robot Ecology (DRE), which was originally developed based on ethnographic studies with vacuum cleaning robots, and for data interpretation we base our work on a newly proposed sociological framework, we call everyday-life centered approach (ELCA).","PeriodicalId":130190,"journal":{"name":"Proceedings of the 11th PErvasive Technologies Related to Assistive Environments Conference","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116963706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Small lot sizes in modern manufacturing present new challenges for people doing complex manual assembly tasks, as every item produced may be different. Assistance systems can support people assembling different variants and reduce stress, while also reducing the number of errors. This paper reports on a qualitative study which used interviews and thematic analysis to study the experiences of one company with an innovative system designed to support workers assembling small lot sizes. The system provides photographs and instructions to people doing manual assembly of engines. The study was done after an extended pilot, and before the next release that will be rolled out to the main assembly lines. The goal of the study was to understand the needs and problems in practice in order to support people developing the next generation of these types of systems. The results highlight the importance of integrating these systems with existing systems, but also the way in which the way the information is delivered depends on the primary goal, e.g. supporting different variants, new workers or quality.
{"title":"Experiences with an Assistive System for Manual Assembly","authors":"Jean D. Hallewell Haslwanter, Boban Blazevski","doi":"10.1145/3197768.3203173","DOIUrl":"https://doi.org/10.1145/3197768.3203173","url":null,"abstract":"Small lot sizes in modern manufacturing present new challenges for people doing complex manual assembly tasks, as every item produced may be different. Assistance systems can support people assembling different variants and reduce stress, while also reducing the number of errors. This paper reports on a qualitative study which used interviews and thematic analysis to study the experiences of one company with an innovative system designed to support workers assembling small lot sizes. The system provides photographs and instructions to people doing manual assembly of engines. The study was done after an extended pilot, and before the next release that will be rolled out to the main assembly lines. The goal of the study was to understand the needs and problems in practice in order to support people developing the next generation of these types of systems. The results highlight the importance of integrating these systems with existing systems, but also the way in which the way the information is delivered depends on the primary goal, e.g. supporting different variants, new workers or quality.","PeriodicalId":130190,"journal":{"name":"Proceedings of the 11th PErvasive Technologies Related to Assistive Environments Conference","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114584468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Medical data can be mined for patterns, which may be used to predict candidate diagnoses according to symptoms and other parameters of care. Our hypothesis is that the admission (initial) patient assessment, when combined with seasonal information can provide more accurate insights for the patient diagnosis. For instance, when cough is the symptom, the probability for flu could be higher during the winter (flu season). We hereby present a method to estimate the temporal variation of the probability for a diagnosis, when the initial patient assessment is known. In order to develop the model, we utilized a large synthetic medical claims dataset from the Centers for Medicare and Medicaid Services. We used the Apriori algorithm to calculate the support and confidence for each 'admission_diagnosis~final_diagnosis' itemset. For each itemset, 52 rules were generated, one for each week of a calendar year. The Apriori output was filtered so that only itemsets with the 'admission diagnosis' on the Left Hand Side(LHS) are extracted. We furthermore smoothened, using the Exponentially Weighted Moving Average (EWMA) algorithm, and then visualized the week-by-week variability of confidence, for any 'admission_diagnosis~fmal_diagnosis' pair of interest. With our approach, researchers can observe seasonal variations of the diagnosis element, and further study these variations for causal knowledge discovery.
{"title":"Temporal Modification of Apriori to find Seasonal Variations between Symptoms and Diagnoses","authors":"Aashara Shrestha, L. Fegaras, D. Zikos","doi":"10.1145/3197768.3201562","DOIUrl":"https://doi.org/10.1145/3197768.3201562","url":null,"abstract":"Medical data can be mined for patterns, which may be used to predict candidate diagnoses according to symptoms and other parameters of care. Our hypothesis is that the admission (initial) patient assessment, when combined with seasonal information can provide more accurate insights for the patient diagnosis. For instance, when cough is the symptom, the probability for flu could be higher during the winter (flu season). We hereby present a method to estimate the temporal variation of the probability for a diagnosis, when the initial patient assessment is known. In order to develop the model, we utilized a large synthetic medical claims dataset from the Centers for Medicare and Medicaid Services. We used the Apriori algorithm to calculate the support and confidence for each 'admission_diagnosis~final_diagnosis' itemset. For each itemset, 52 rules were generated, one for each week of a calendar year. The Apriori output was filtered so that only itemsets with the 'admission diagnosis' on the Left Hand Side(LHS) are extracted. We furthermore smoothened, using the Exponentially Weighted Moving Average (EWMA) algorithm, and then visualized the week-by-week variability of confidence, for any 'admission_diagnosis~fmal_diagnosis' pair of interest. With our approach, researchers can observe seasonal variations of the diagnosis element, and further study these variations for causal knowledge discovery.","PeriodicalId":130190,"journal":{"name":"Proceedings of the 11th PErvasive Technologies Related to Assistive Environments Conference","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117224306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Suad Albawendi, Ahmad Lotfi, Heather Powell, Kofi Appiah
Falls are one of the greatest risks for the older adults living alone at home. This paper presents a novel visual-based fall detection approach to support independent living for older adults. The proposed approach employs three unique features; motion information, human shape variation and projection histogram to detect a fall. Motion information of a segmented silhouette, which when extracted can provide a useful cue for classifying different behaviours. Also, the projection histogram and variation in human shape can be used to describe human body postures and subsequently fall events. The proposed approach presented here extracts motion information, using best-fit approximated ellipse around the human body and in addition projection histogram features to further improve the accuracy of fall detection. Experimental results are presented and show high fall detection rate of 99.81% with partially occluded video data.
{"title":"Video Based Fall Detection using Features of Motion, Shape and Histogram","authors":"Suad Albawendi, Ahmad Lotfi, Heather Powell, Kofi Appiah","doi":"10.1145/3197768.3201539","DOIUrl":"https://doi.org/10.1145/3197768.3201539","url":null,"abstract":"Falls are one of the greatest risks for the older adults living alone at home. This paper presents a novel visual-based fall detection approach to support independent living for older adults. The proposed approach employs three unique features; motion information, human shape variation and projection histogram to detect a fall. Motion information of a segmented silhouette, which when extracted can provide a useful cue for classifying different behaviours. Also, the projection histogram and variation in human shape can be used to describe human body postures and subsequently fall events. The proposed approach presented here extracts motion information, using best-fit approximated ellipse around the human body and in addition projection histogram features to further improve the accuracy of fall detection. Experimental results are presented and show high fall detection rate of 99.81% with partially occluded video data.","PeriodicalId":130190,"journal":{"name":"Proceedings of the 11th PErvasive Technologies Related to Assistive Environments Conference","volume":"48 37","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114006319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：