C. Schneegass
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6 records found
1
People track many parts of daily life, such as steps, heart rate, sleep, and exercise. Consumer EEG devices now make it possible to record electrical signals from the brain outside hospitals and laboratories. Small sensors placed on the scalp collect these signals during everyday activities.
However, EEG feedback is not as easy to interpret as a step count or sleep duration. Applications turn complex signals into simple scores, such as attention, cognitive load, and sleepiness. These scores can be useful, but they can change depending on the person, their activity, the environment, and signal quality. A score therefore cannot fully explain how someone feels or what is happening in their mind.
This thesis explores how consumer EEG feedback can be visualised in a way that helps people understand it. The project was conducted with Axite, the company behind NeuroJournal, an application that works with the Muse S Athena EEG headband. It focuses on self-motivated adults who are interested in using this technology for self-awareness, wellbeing, or productivity.
The research followed a Research through Design approach using the Double Diamond process. The Discover phase included literature research, an online survey with 12 people interested in EEG and self-tracking, and a five-day diary-probe study with 13 participants who had little or no previous experience with consumer EEG. During the study, participants used EEG headbands, recorded their daily situation through diary questions, and reflected on what they expected their results to show. At the end of the study, they reviewed their results in a reflection interview, card-sort activity, and co-creation session.
The research helped uncover three main areas. First, it showed how people try to make sense of consumer EEG feedback and where they struggle. Participants did not understand scores or graphs in isolation. They needed to connect a result with sleep, mood, stress, activity, events during the day, and how they felt at that moment. Second, it revealed which types of visualisation and support could help them: personal baselines, comparisons over time, simple explanations, context next to a score, and the ability to look deeper into a result when needed. Third, it showed that people have different reasons for using EEG technology. Some were curious about how their brain works, while others wanted to understand habits, support meditation, reduce stress, or improve productivity.
These findings were translated into six design principles for reflective EEG visualisation. They guided the design of a post-session experience for NeuroJournal. Instead of showing a score as a final judgement, the proposed experience invites users to explore it. It helps them compare results with their own usual pattern, review relevant context, understand what a metric means, check signal quality, and answer questions about what may have influenced the result. ...
However, EEG feedback is not as easy to interpret as a step count or sleep duration. Applications turn complex signals into simple scores, such as attention, cognitive load, and sleepiness. These scores can be useful, but they can change depending on the person, their activity, the environment, and signal quality. A score therefore cannot fully explain how someone feels or what is happening in their mind.
This thesis explores how consumer EEG feedback can be visualised in a way that helps people understand it. The project was conducted with Axite, the company behind NeuroJournal, an application that works with the Muse S Athena EEG headband. It focuses on self-motivated adults who are interested in using this technology for self-awareness, wellbeing, or productivity.
The research followed a Research through Design approach using the Double Diamond process. The Discover phase included literature research, an online survey with 12 people interested in EEG and self-tracking, and a five-day diary-probe study with 13 participants who had little or no previous experience with consumer EEG. During the study, participants used EEG headbands, recorded their daily situation through diary questions, and reflected on what they expected their results to show. At the end of the study, they reviewed their results in a reflection interview, card-sort activity, and co-creation session.
The research helped uncover three main areas. First, it showed how people try to make sense of consumer EEG feedback and where they struggle. Participants did not understand scores or graphs in isolation. They needed to connect a result with sleep, mood, stress, activity, events during the day, and how they felt at that moment. Second, it revealed which types of visualisation and support could help them: personal baselines, comparisons over time, simple explanations, context next to a score, and the ability to look deeper into a result when needed. Third, it showed that people have different reasons for using EEG technology. Some were curious about how their brain works, while others wanted to understand habits, support meditation, reduce stress, or improve productivity.
These findings were translated into six design principles for reflective EEG visualisation. They guided the design of a post-session experience for NeuroJournal. Instead of showing a score as a final judgement, the proposed experience invites users to explore it. It helps them compare results with their own usual pattern, review relevant context, understand what a metric means, check signal quality, and answer questions about what may have influenced the result. ...
People track many parts of daily life, such as steps, heart rate, sleep, and exercise. Consumer EEG devices now make it possible to record electrical signals from the brain outside hospitals and laboratories. Small sensors placed on the scalp collect these signals during everyday activities.
However, EEG feedback is not as easy to interpret as a step count or sleep duration. Applications turn complex signals into simple scores, such as attention, cognitive load, and sleepiness. These scores can be useful, but they can change depending on the person, their activity, the environment, and signal quality. A score therefore cannot fully explain how someone feels or what is happening in their mind.
This thesis explores how consumer EEG feedback can be visualised in a way that helps people understand it. The project was conducted with Axite, the company behind NeuroJournal, an application that works with the Muse S Athena EEG headband. It focuses on self-motivated adults who are interested in using this technology for self-awareness, wellbeing, or productivity.
The research followed a Research through Design approach using the Double Diamond process. The Discover phase included literature research, an online survey with 12 people interested in EEG and self-tracking, and a five-day diary-probe study with 13 participants who had little or no previous experience with consumer EEG. During the study, participants used EEG headbands, recorded their daily situation through diary questions, and reflected on what they expected their results to show. At the end of the study, they reviewed their results in a reflection interview, card-sort activity, and co-creation session.
The research helped uncover three main areas. First, it showed how people try to make sense of consumer EEG feedback and where they struggle. Participants did not understand scores or graphs in isolation. They needed to connect a result with sleep, mood, stress, activity, events during the day, and how they felt at that moment. Second, it revealed which types of visualisation and support could help them: personal baselines, comparisons over time, simple explanations, context next to a score, and the ability to look deeper into a result when needed. Third, it showed that people have different reasons for using EEG technology. Some were curious about how their brain works, while others wanted to understand habits, support meditation, reduce stress, or improve productivity.
These findings were translated into six design principles for reflective EEG visualisation. They guided the design of a post-session experience for NeuroJournal. Instead of showing a score as a final judgement, the proposed experience invites users to explore it. It helps them compare results with their own usual pattern, review relevant context, understand what a metric means, check signal quality, and answer questions about what may have influenced the result.
However, EEG feedback is not as easy to interpret as a step count or sleep duration. Applications turn complex signals into simple scores, such as attention, cognitive load, and sleepiness. These scores can be useful, but they can change depending on the person, their activity, the environment, and signal quality. A score therefore cannot fully explain how someone feels or what is happening in their mind.
This thesis explores how consumer EEG feedback can be visualised in a way that helps people understand it. The project was conducted with Axite, the company behind NeuroJournal, an application that works with the Muse S Athena EEG headband. It focuses on self-motivated adults who are interested in using this technology for self-awareness, wellbeing, or productivity.
The research followed a Research through Design approach using the Double Diamond process. The Discover phase included literature research, an online survey with 12 people interested in EEG and self-tracking, and a five-day diary-probe study with 13 participants who had little or no previous experience with consumer EEG. During the study, participants used EEG headbands, recorded their daily situation through diary questions, and reflected on what they expected their results to show. At the end of the study, they reviewed their results in a reflection interview, card-sort activity, and co-creation session.
The research helped uncover three main areas. First, it showed how people try to make sense of consumer EEG feedback and where they struggle. Participants did not understand scores or graphs in isolation. They needed to connect a result with sleep, mood, stress, activity, events during the day, and how they felt at that moment. Second, it revealed which types of visualisation and support could help them: personal baselines, comparisons over time, simple explanations, context next to a score, and the ability to look deeper into a result when needed. Third, it showed that people have different reasons for using EEG technology. Some were curious about how their brain works, while others wanted to understand habits, support meditation, reduce stress, or improve productivity.
These findings were translated into six design principles for reflective EEG visualisation. They guided the design of a post-session experience for NeuroJournal. Instead of showing a score as a final judgement, the proposed experience invites users to explore it. It helps them compare results with their own usual pattern, review relevant context, understand what a metric means, check signal quality, and answer questions about what may have influenced the result.
This report outlines the design of an interactive reading assistance system aimed at enhancing reading efficiency and experience for individuals with dyslexia.
The design process is divided into four phases: Discover, Define, Develop, and Deliver.
The Discover phase includes literature and technical research. To achieve the design goal, eye-tracking technology combined with AI generation was identified as an ideal combination for intuitive information exchange and analysis during the research.
After finishing the design definition, the research involved a comprehensive iterative design process, incorporating insights from functional tests, user interviews, an expert interview, and a technical focus group. A notable innovation is the use of reading data from eye movements, integrated with AI to provide real-time personalized reading assistance.The powerful capabilities of AI bring unlimited possibilities for the system's flexibility. To this end, a comprehensive strategic roadmap and system map were also designed to ensure the feasibility of the project.
Despite its innovative approach, the project faced challenges, including workload constraints and technical hurdles, which affected the thoroughness of verification and validation. These limitations highlight areas for further development and refinement. By addressing the challenges, this project has the potential to influence broader accessibility practices in digital reading. ...
The design process is divided into four phases: Discover, Define, Develop, and Deliver.
The Discover phase includes literature and technical research. To achieve the design goal, eye-tracking technology combined with AI generation was identified as an ideal combination for intuitive information exchange and analysis during the research.
After finishing the design definition, the research involved a comprehensive iterative design process, incorporating insights from functional tests, user interviews, an expert interview, and a technical focus group. A notable innovation is the use of reading data from eye movements, integrated with AI to provide real-time personalized reading assistance.The powerful capabilities of AI bring unlimited possibilities for the system's flexibility. To this end, a comprehensive strategic roadmap and system map were also designed to ensure the feasibility of the project.
Despite its innovative approach, the project faced challenges, including workload constraints and technical hurdles, which affected the thoroughness of verification and validation. These limitations highlight areas for further development and refinement. By addressing the challenges, this project has the potential to influence broader accessibility practices in digital reading. ...
This report outlines the design of an interactive reading assistance system aimed at enhancing reading efficiency and experience for individuals with dyslexia.
The design process is divided into four phases: Discover, Define, Develop, and Deliver.
The Discover phase includes literature and technical research. To achieve the design goal, eye-tracking technology combined with AI generation was identified as an ideal combination for intuitive information exchange and analysis during the research.
After finishing the design definition, the research involved a comprehensive iterative design process, incorporating insights from functional tests, user interviews, an expert interview, and a technical focus group. A notable innovation is the use of reading data from eye movements, integrated with AI to provide real-time personalized reading assistance.The powerful capabilities of AI bring unlimited possibilities for the system's flexibility. To this end, a comprehensive strategic roadmap and system map were also designed to ensure the feasibility of the project.
Despite its innovative approach, the project faced challenges, including workload constraints and technical hurdles, which affected the thoroughness of verification and validation. These limitations highlight areas for further development and refinement. By addressing the challenges, this project has the potential to influence broader accessibility practices in digital reading.
The design process is divided into four phases: Discover, Define, Develop, and Deliver.
The Discover phase includes literature and technical research. To achieve the design goal, eye-tracking technology combined with AI generation was identified as an ideal combination for intuitive information exchange and analysis during the research.
After finishing the design definition, the research involved a comprehensive iterative design process, incorporating insights from functional tests, user interviews, an expert interview, and a technical focus group. A notable innovation is the use of reading data from eye movements, integrated with AI to provide real-time personalized reading assistance.The powerful capabilities of AI bring unlimited possibilities for the system's flexibility. To this end, a comprehensive strategic roadmap and system map were also designed to ensure the feasibility of the project.
Despite its innovative approach, the project faced challenges, including workload constraints and technical hurdles, which affected the thoroughness of verification and validation. These limitations highlight areas for further development and refinement. By addressing the challenges, this project has the potential to influence broader accessibility practices in digital reading.
Deceptive design patterns (also known as 'dark patterns') are design elements that trick users into unintended behaviors that harm them and benefit the party implementing the design. Prior work has taxonomized, investigated, and speculated the presence of dark patterns across environments (applications, websites, games, VR, AR, IoT) and modalities (visual, audio). However, more attention is needed to investigate how haptic technologies might be used to enable deceptive patterns since it is gradually becoming prevalent in digital experiences.
This project contributes to the characterization and demonstration of deceptive patterns enabled / augmented by haptic stimulation. First, we identify the key characteristics of haptic modality that may enable new dark patterns or argument existing ones, and we surface examples of such patterns. Second, we conducted a between-group study ,in which we investigated the efficacy of one chosen haptic dark pattern. In addition, we presented mitigative recommendations to the stakeholders.
...
This project contributes to the characterization and demonstration of deceptive patterns enabled / augmented by haptic stimulation. First, we identify the key characteristics of haptic modality that may enable new dark patterns or argument existing ones, and we surface examples of such patterns. Second, we conducted a between-group study ,in which we investigated the efficacy of one chosen haptic dark pattern. In addition, we presented mitigative recommendations to the stakeholders.
...
Deceptive design patterns (also known as 'dark patterns') are design elements that trick users into unintended behaviors that harm them and benefit the party implementing the design. Prior work has taxonomized, investigated, and speculated the presence of dark patterns across environments (applications, websites, games, VR, AR, IoT) and modalities (visual, audio). However, more attention is needed to investigate how haptic technologies might be used to enable deceptive patterns since it is gradually becoming prevalent in digital experiences.
This project contributes to the characterization and demonstration of deceptive patterns enabled / augmented by haptic stimulation. First, we identify the key characteristics of haptic modality that may enable new dark patterns or argument existing ones, and we surface examples of such patterns. Second, we conducted a between-group study ,in which we investigated the efficacy of one chosen haptic dark pattern. In addition, we presented mitigative recommendations to the stakeholders.
This project contributes to the characterization and demonstration of deceptive patterns enabled / augmented by haptic stimulation. First, we identify the key characteristics of haptic modality that may enable new dark patterns or argument existing ones, and we surface examples of such patterns. Second, we conducted a between-group study ,in which we investigated the efficacy of one chosen haptic dark pattern. In addition, we presented mitigative recommendations to the stakeholders.
Integrating cognitive user data in journey maps
Explorations towards designer affinity
User-centric design practice rely on journey maps and personas as a way to communicate user needs to the design team (Lanius et al., 2021). However, journey maps in practice have been found to lack a dimension that could inform designers about intrinsic cognitive needs of the user. This research project aims to address this gap by exploring ways to make human cognitive data designer-friendly. Through multi-study approach, including the Research through Design (RtD) (Godin & Zahedi, 2014) method, the study investigates dimensions of the relationship between designers and cognitive user data to make it easy-to-approach in future.
Following the context exploration studies, designers' perspectives and practices regarding cognitive user data are delved into. Findings from exploratory interviews reveal varied interpretations of cognitive data, challenges in accessing and visualizing data, and a keen interest in its potential benefits for design processes. Designers identify time constraints as a major hurdle but express enthusiasm for the posterity and revisiting advantages of effective cognitive data visualization.
The RtD method helps in investigating a way of presenting holistic data to designer that merges intrinsic and extrinsic factors of the user. Designers favor clarity, interactive exploration, and reliability in data presentation. The study provides a comprehensive list of neurophysiological measures that can aid designers in decision-making. Additionally, insights into designers' thinking styles, distinguishing between big-picture and detail-oriented thinkers, add a nuanced layer to understanding their affinity with cognitive data.
The report acknowledges limitations, including biases in the Research-through-Design method, reliance on self-reported data, and the controlled environment of prototype evaluations. Future research is encouraged to address these limitations and enhance the ecological validity of findings.
In conclusion, this research offers valuable insights into integrating cognitive user data within designer practices and establishes a way of integrating observational data with user journey maps. The findings provide a foundation for developing tools and approaches that align with designers' preferences, ultimately enriching the design process through meaningful integration of cognitive insights.
...
Following the context exploration studies, designers' perspectives and practices regarding cognitive user data are delved into. Findings from exploratory interviews reveal varied interpretations of cognitive data, challenges in accessing and visualizing data, and a keen interest in its potential benefits for design processes. Designers identify time constraints as a major hurdle but express enthusiasm for the posterity and revisiting advantages of effective cognitive data visualization.
The RtD method helps in investigating a way of presenting holistic data to designer that merges intrinsic and extrinsic factors of the user. Designers favor clarity, interactive exploration, and reliability in data presentation. The study provides a comprehensive list of neurophysiological measures that can aid designers in decision-making. Additionally, insights into designers' thinking styles, distinguishing between big-picture and detail-oriented thinkers, add a nuanced layer to understanding their affinity with cognitive data.
The report acknowledges limitations, including biases in the Research-through-Design method, reliance on self-reported data, and the controlled environment of prototype evaluations. Future research is encouraged to address these limitations and enhance the ecological validity of findings.
In conclusion, this research offers valuable insights into integrating cognitive user data within designer practices and establishes a way of integrating observational data with user journey maps. The findings provide a foundation for developing tools and approaches that align with designers' preferences, ultimately enriching the design process through meaningful integration of cognitive insights.
...
User-centric design practice rely on journey maps and personas as a way to communicate user needs to the design team (Lanius et al., 2021). However, journey maps in practice have been found to lack a dimension that could inform designers about intrinsic cognitive needs of the user. This research project aims to address this gap by exploring ways to make human cognitive data designer-friendly. Through multi-study approach, including the Research through Design (RtD) (Godin & Zahedi, 2014) method, the study investigates dimensions of the relationship between designers and cognitive user data to make it easy-to-approach in future.
Following the context exploration studies, designers' perspectives and practices regarding cognitive user data are delved into. Findings from exploratory interviews reveal varied interpretations of cognitive data, challenges in accessing and visualizing data, and a keen interest in its potential benefits for design processes. Designers identify time constraints as a major hurdle but express enthusiasm for the posterity and revisiting advantages of effective cognitive data visualization.
The RtD method helps in investigating a way of presenting holistic data to designer that merges intrinsic and extrinsic factors of the user. Designers favor clarity, interactive exploration, and reliability in data presentation. The study provides a comprehensive list of neurophysiological measures that can aid designers in decision-making. Additionally, insights into designers' thinking styles, distinguishing between big-picture and detail-oriented thinkers, add a nuanced layer to understanding their affinity with cognitive data.
The report acknowledges limitations, including biases in the Research-through-Design method, reliance on self-reported data, and the controlled environment of prototype evaluations. Future research is encouraged to address these limitations and enhance the ecological validity of findings.
In conclusion, this research offers valuable insights into integrating cognitive user data within designer practices and establishes a way of integrating observational data with user journey maps. The findings provide a foundation for developing tools and approaches that align with designers' preferences, ultimately enriching the design process through meaningful integration of cognitive insights.
Following the context exploration studies, designers' perspectives and practices regarding cognitive user data are delved into. Findings from exploratory interviews reveal varied interpretations of cognitive data, challenges in accessing and visualizing data, and a keen interest in its potential benefits for design processes. Designers identify time constraints as a major hurdle but express enthusiasm for the posterity and revisiting advantages of effective cognitive data visualization.
The RtD method helps in investigating a way of presenting holistic data to designer that merges intrinsic and extrinsic factors of the user. Designers favor clarity, interactive exploration, and reliability in data presentation. The study provides a comprehensive list of neurophysiological measures that can aid designers in decision-making. Additionally, insights into designers' thinking styles, distinguishing between big-picture and detail-oriented thinkers, add a nuanced layer to understanding their affinity with cognitive data.
The report acknowledges limitations, including biases in the Research-through-Design method, reliance on self-reported data, and the controlled environment of prototype evaluations. Future research is encouraged to address these limitations and enhance the ecological validity of findings.
In conclusion, this research offers valuable insights into integrating cognitive user data within designer practices and establishes a way of integrating observational data with user journey maps. The findings provide a foundation for developing tools and approaches that align with designers' preferences, ultimately enriching the design process through meaningful integration of cognitive insights.
Master thesis
(2024)
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S. Brenes Piza, M. Melles, C. Schneegass, Tilman Dingler, Ineke J.M. van der Ham
This thesis explores design interventions for individuals with Developmental Topographical Disorientation (DTD) and others with weak navigational skills. “DTD refers to the lifelong inability to orient in extremely familiar surroundings despite the absence of any acquired brain damage or neurological disorder” (Iaria & Burles, 2016) This research focused on addressing the gap between allocentric navigation (map-based, provided by technology) and egocentric navigation (personal perspective), which many individuals with DTD struggle to translate effectively in their daily life.
The research goal was to explore how to better support people with DTD, as well as others with below average navigational skills, in bridging the gap between these two navigational perspectives. Interviews with students and recent graduates who self-identified as having poor navigational skills revealed low spatial anxiety, likely due to their reliance on GPS. Based on these interviews and navigation technology research, wayfinding guidelines were developed, emphasizing clear visual landmarks that simplify the cognitive translation between map-based and personal navigation.
A design concept was created which presents the directions to take in a landmark based map, with a song as a mnemonic aid to learn the navigation instruction. Focusing on how individuals use both allocentric and egocentric perspectives to navigate an evaluation with participants who self identify as not having good navigation skills, navigated a virtual environment using the concept. Results showed that while a multisensory approach can be useful, clear and simple visual cues, such as the selection of one specific landmark per decision point, are more effective in aiding navigation.
In conclusion, the study shows design guidelines to simplify the transition between allocentric and egocentric navigation, and to motivate the user to memorize the route rather than relying solely on technology or multisensory tools. It also highlights the need for greater awareness of DTD and offers insights into designing accessible, user-centered navigation tools. ...
This thesis explores design interventions for individuals with Developmental Topographical Disorientation (DTD) and others with weak navigational skills. “DTD refers to the lifelong inability to orient in extremely familiar surroundings despite the absence of any acquired brain damage or neurological disorder” (Iaria & Burles, 2016) This research focused on addressing the gap between allocentric navigation (map-based, provided by technology) and egocentric navigation (personal perspective), which many individuals with DTD struggle to translate effectively in their daily life.
The research goal was to explore how to better support people with DTD, as well as others with below average navigational skills, in bridging the gap between these two navigational perspectives. Interviews with students and recent graduates who self-identified as having poor navigational skills revealed low spatial anxiety, likely due to their reliance on GPS. Based on these interviews and navigation technology research, wayfinding guidelines were developed, emphasizing clear visual landmarks that simplify the cognitive translation between map-based and personal navigation.
A design concept was created which presents the directions to take in a landmark based map, with a song as a mnemonic aid to learn the navigation instruction. Focusing on how individuals use both allocentric and egocentric perspectives to navigate an evaluation with participants who self identify as not having good navigation skills, navigated a virtual environment using the concept. Results showed that while a multisensory approach can be useful, clear and simple visual cues, such as the selection of one specific landmark per decision point, are more effective in aiding navigation.
In conclusion, the study shows design guidelines to simplify the transition between allocentric and egocentric navigation, and to motivate the user to memorize the route rather than relying solely on technology or multisensory tools. It also highlights the need for greater awareness of DTD and offers insights into designing accessible, user-centered navigation tools.
Cooking is an essential part of most people’s day-to-day lives. It is a dynamic activity that involves multitasking, timing of tasks, and flexibility. However, the available instruction methods for cooks who wish to follow recipes are quite rigid and linear. This project aims to create a design solution that provides instructions in a way that is in better accordance with natural cooking behaviours.
The scope of the project is to deliver a conceptual instruction-based cooking tool that utilizes Artificial Intelligence. While designing the solution, speculative design methods are considered in order to design for the near future. It is designed for a future where tasks in recipe instructions can be used more flexibly in digital products and Human Activity Recognition can accurately recognize complex cooking actions with mobile devices. The design solution has been created for a company called Verdify. Verdify is a food tech company with products that aim to allow users to achieve fully personalized nutrition. Swapmeals is their recipe platform that allows users to swap ingredients to fit their dietary needs while adjusting instructions accordingly and maintaining flavour profiles. The design solution aims to ultimately live on this recipe platform. The project is executed with a User-centered Design approach which involves end-users in the design process in order for them to have an impact on their final product.
The users were observed while cooking with instructions in order to understand the pain points that should be designed for. The most prevalent and significant themes that emerged from the study were that users experience cognitive overload while cooking and often experience uncertainty in the cooking process.
Academic design solutions and commercial products for hands-free instruction-based cooking were reviewed to understand which issues, discovered in the context research, have not been designed for. This gap is used to specify design requirements. The requirements specify that the design solution should allow home-cooks to use recipe instructions in a way that is hands-free, non-linear, informative, and that minimally interrupts the cooking flow along with reducing their cognitive load and the associated negative emotions. The solution is also required to allow the user to mainly focus on the task at hand; the device should manage the remaining responsibilities. Lastly, the research discovered that the design solution should create the experience of cooking a new recipe similarly to how one would cook a familiar recipe.
Solutions were explored that meet the specified requirements. The exploration led to 2 contrasting concepts that aim to improve instruction-based cooking in a familiar textual manner and an innovative experiential manner. These 2 concepts were tested with users in order to compare the newly defined interaction methods and understand which interactions are desired in the various moments of the cooking process. The results generated an iterated list of requirements to be applied to the final design.
Lastly, a conceptual instruction-based cooking design solution was introduced; a user interface that utilizes Human Activity Recognition for user-to-product communication. The tool adopts the cognitive load from its users by managing timing and their progression while adjusting to the user’s autonomous adaptations to the recipe. The design solution is an interactive, hands-free, and informative recipe instruction solution. It allows home-cooks to let go of keeping an overview of the cooking process and instead solely focus on the task at hand, allowing cooking to be a worry-free and enjoyable activity for even the tensest home-cooks. ...
The scope of the project is to deliver a conceptual instruction-based cooking tool that utilizes Artificial Intelligence. While designing the solution, speculative design methods are considered in order to design for the near future. It is designed for a future where tasks in recipe instructions can be used more flexibly in digital products and Human Activity Recognition can accurately recognize complex cooking actions with mobile devices. The design solution has been created for a company called Verdify. Verdify is a food tech company with products that aim to allow users to achieve fully personalized nutrition. Swapmeals is their recipe platform that allows users to swap ingredients to fit their dietary needs while adjusting instructions accordingly and maintaining flavour profiles. The design solution aims to ultimately live on this recipe platform. The project is executed with a User-centered Design approach which involves end-users in the design process in order for them to have an impact on their final product.
The users were observed while cooking with instructions in order to understand the pain points that should be designed for. The most prevalent and significant themes that emerged from the study were that users experience cognitive overload while cooking and often experience uncertainty in the cooking process.
Academic design solutions and commercial products for hands-free instruction-based cooking were reviewed to understand which issues, discovered in the context research, have not been designed for. This gap is used to specify design requirements. The requirements specify that the design solution should allow home-cooks to use recipe instructions in a way that is hands-free, non-linear, informative, and that minimally interrupts the cooking flow along with reducing their cognitive load and the associated negative emotions. The solution is also required to allow the user to mainly focus on the task at hand; the device should manage the remaining responsibilities. Lastly, the research discovered that the design solution should create the experience of cooking a new recipe similarly to how one would cook a familiar recipe.
Solutions were explored that meet the specified requirements. The exploration led to 2 contrasting concepts that aim to improve instruction-based cooking in a familiar textual manner and an innovative experiential manner. These 2 concepts were tested with users in order to compare the newly defined interaction methods and understand which interactions are desired in the various moments of the cooking process. The results generated an iterated list of requirements to be applied to the final design.
Lastly, a conceptual instruction-based cooking design solution was introduced; a user interface that utilizes Human Activity Recognition for user-to-product communication. The tool adopts the cognitive load from its users by managing timing and their progression while adjusting to the user’s autonomous adaptations to the recipe. The design solution is an interactive, hands-free, and informative recipe instruction solution. It allows home-cooks to let go of keeping an overview of the cooking process and instead solely focus on the task at hand, allowing cooking to be a worry-free and enjoyable activity for even the tensest home-cooks. ...
Cooking is an essential part of most people’s day-to-day lives. It is a dynamic activity that involves multitasking, timing of tasks, and flexibility. However, the available instruction methods for cooks who wish to follow recipes are quite rigid and linear. This project aims to create a design solution that provides instructions in a way that is in better accordance with natural cooking behaviours.
The scope of the project is to deliver a conceptual instruction-based cooking tool that utilizes Artificial Intelligence. While designing the solution, speculative design methods are considered in order to design for the near future. It is designed for a future where tasks in recipe instructions can be used more flexibly in digital products and Human Activity Recognition can accurately recognize complex cooking actions with mobile devices. The design solution has been created for a company called Verdify. Verdify is a food tech company with products that aim to allow users to achieve fully personalized nutrition. Swapmeals is their recipe platform that allows users to swap ingredients to fit their dietary needs while adjusting instructions accordingly and maintaining flavour profiles. The design solution aims to ultimately live on this recipe platform. The project is executed with a User-centered Design approach which involves end-users in the design process in order for them to have an impact on their final product.
The users were observed while cooking with instructions in order to understand the pain points that should be designed for. The most prevalent and significant themes that emerged from the study were that users experience cognitive overload while cooking and often experience uncertainty in the cooking process.
Academic design solutions and commercial products for hands-free instruction-based cooking were reviewed to understand which issues, discovered in the context research, have not been designed for. This gap is used to specify design requirements. The requirements specify that the design solution should allow home-cooks to use recipe instructions in a way that is hands-free, non-linear, informative, and that minimally interrupts the cooking flow along with reducing their cognitive load and the associated negative emotions. The solution is also required to allow the user to mainly focus on the task at hand; the device should manage the remaining responsibilities. Lastly, the research discovered that the design solution should create the experience of cooking a new recipe similarly to how one would cook a familiar recipe.
Solutions were explored that meet the specified requirements. The exploration led to 2 contrasting concepts that aim to improve instruction-based cooking in a familiar textual manner and an innovative experiential manner. These 2 concepts were tested with users in order to compare the newly defined interaction methods and understand which interactions are desired in the various moments of the cooking process. The results generated an iterated list of requirements to be applied to the final design.
Lastly, a conceptual instruction-based cooking design solution was introduced; a user interface that utilizes Human Activity Recognition for user-to-product communication. The tool adopts the cognitive load from its users by managing timing and their progression while adjusting to the user’s autonomous adaptations to the recipe. The design solution is an interactive, hands-free, and informative recipe instruction solution. It allows home-cooks to let go of keeping an overview of the cooking process and instead solely focus on the task at hand, allowing cooking to be a worry-free and enjoyable activity for even the tensest home-cooks.
The scope of the project is to deliver a conceptual instruction-based cooking tool that utilizes Artificial Intelligence. While designing the solution, speculative design methods are considered in order to design for the near future. It is designed for a future where tasks in recipe instructions can be used more flexibly in digital products and Human Activity Recognition can accurately recognize complex cooking actions with mobile devices. The design solution has been created for a company called Verdify. Verdify is a food tech company with products that aim to allow users to achieve fully personalized nutrition. Swapmeals is their recipe platform that allows users to swap ingredients to fit their dietary needs while adjusting instructions accordingly and maintaining flavour profiles. The design solution aims to ultimately live on this recipe platform. The project is executed with a User-centered Design approach which involves end-users in the design process in order for them to have an impact on their final product.
The users were observed while cooking with instructions in order to understand the pain points that should be designed for. The most prevalent and significant themes that emerged from the study were that users experience cognitive overload while cooking and often experience uncertainty in the cooking process.
Academic design solutions and commercial products for hands-free instruction-based cooking were reviewed to understand which issues, discovered in the context research, have not been designed for. This gap is used to specify design requirements. The requirements specify that the design solution should allow home-cooks to use recipe instructions in a way that is hands-free, non-linear, informative, and that minimally interrupts the cooking flow along with reducing their cognitive load and the associated negative emotions. The solution is also required to allow the user to mainly focus on the task at hand; the device should manage the remaining responsibilities. Lastly, the research discovered that the design solution should create the experience of cooking a new recipe similarly to how one would cook a familiar recipe.
Solutions were explored that meet the specified requirements. The exploration led to 2 contrasting concepts that aim to improve instruction-based cooking in a familiar textual manner and an innovative experiential manner. These 2 concepts were tested with users in order to compare the newly defined interaction methods and understand which interactions are desired in the various moments of the cooking process. The results generated an iterated list of requirements to be applied to the final design.
Lastly, a conceptual instruction-based cooking design solution was introduced; a user interface that utilizes Human Activity Recognition for user-to-product communication. The tool adopts the cognitive load from its users by managing timing and their progression while adjusting to the user’s autonomous adaptations to the recipe. The design solution is an interactive, hands-free, and informative recipe instruction solution. It allows home-cooks to let go of keeping an overview of the cooking process and instead solely focus on the task at hand, allowing cooking to be a worry-free and enjoyable activity for even the tensest home-cooks.