AJ
A.H. Jellema
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1
The warehousing sector is among the top when it comes to the risk of developing work-related musculoskeletal disorders (WMSDs), in particular low back pain (LBP). In this sector, LBP is a prevalent issue, due to the nature of the job of lifting and moving (heavy) objects around. The issue has significant implications for the workers’ health, in terms of quality of life. Companies and society feel the consequences in terms of financial costs. This issue could be tackled by introducing smart technology in the form of a smart safety shoe. The concept has been developed by a strategic product design student and the strategic direction has been determined. This project explores the concept further and validates the idea of smart safety shoes to reduce the risk of LBP during manual handling, through technological means.
To understand the problem of LBP in context, extensive literature research was conducted on ergonomics. Understanding what causes it and the current methods to reduce the risks. Further, looking into the possibility of detecting causes through technology. The research results were used to build a prototype for validation of the concept.
The causality of LBP is not easy to point out, as multiple factors (physical, psychosocial, and individual) play a role in its development. Research does conclude that physical factors play a major role, which is related to heavy lifting, repetitiveness, and awkward postures. Manual handling can be performed safely as long as the weight is below 23 kg and correct postures are adopted. Though not all workers adhere to correct posture, and it is hard to track through observational methods.
Postures can be tracked or detected through plantar pressure distribution (PPD), by using pressure sensors. These sensors can be placed within safety shoes and will collect PPD data of workers. The PPD data shows certain patterns and have characteristics that can be linked to different postures. The data can be analysed using machine learning, to automate the process and could be able to give feedback to the user when a risky posture is adopted.
A pressure insole has been prototyped with the conducted research to collect PPD data of different postures (stoop lifting, lifting above shoulder height, and asymmetrical lifting). The collected data were manually analysed to understand how patterns may look like. A machine learning model was made, using a tree algorithm, to analyse the data as well. It can classify all the measured static postures with 100% accuracy. Dynamic lifting data were not analysed by the model yet as it needs additional data preparation. At this point, the concept needs more development to analyse dynamic data and to implement the hardware in the safety shoes.
Based on the results, the core components of the concept have been proven to work and able to detect different postures with great accuracy. The idea of a smart safety shoe that can detect and warn the worker of potential injury is not far-fetched.
This project is the first step in the development of the concept. Due to the complexity of the issue and required knowledge, additional research is needed for the continuation of the project. The posture database has to be set up, improving the machine learning model for dynamic lifting data, hardware design and a live feedback system. With these developments, a smart safety shoe could be brought to market that could improve workers' lives and save additional costs for companies. ...
To understand the problem of LBP in context, extensive literature research was conducted on ergonomics. Understanding what causes it and the current methods to reduce the risks. Further, looking into the possibility of detecting causes through technology. The research results were used to build a prototype for validation of the concept.
The causality of LBP is not easy to point out, as multiple factors (physical, psychosocial, and individual) play a role in its development. Research does conclude that physical factors play a major role, which is related to heavy lifting, repetitiveness, and awkward postures. Manual handling can be performed safely as long as the weight is below 23 kg and correct postures are adopted. Though not all workers adhere to correct posture, and it is hard to track through observational methods.
Postures can be tracked or detected through plantar pressure distribution (PPD), by using pressure sensors. These sensors can be placed within safety shoes and will collect PPD data of workers. The PPD data shows certain patterns and have characteristics that can be linked to different postures. The data can be analysed using machine learning, to automate the process and could be able to give feedback to the user when a risky posture is adopted.
A pressure insole has been prototyped with the conducted research to collect PPD data of different postures (stoop lifting, lifting above shoulder height, and asymmetrical lifting). The collected data were manually analysed to understand how patterns may look like. A machine learning model was made, using a tree algorithm, to analyse the data as well. It can classify all the measured static postures with 100% accuracy. Dynamic lifting data were not analysed by the model yet as it needs additional data preparation. At this point, the concept needs more development to analyse dynamic data and to implement the hardware in the safety shoes.
Based on the results, the core components of the concept have been proven to work and able to detect different postures with great accuracy. The idea of a smart safety shoe that can detect and warn the worker of potential injury is not far-fetched.
This project is the first step in the development of the concept. Due to the complexity of the issue and required knowledge, additional research is needed for the continuation of the project. The posture database has to be set up, improving the machine learning model for dynamic lifting data, hardware design and a live feedback system. With these developments, a smart safety shoe could be brought to market that could improve workers' lives and save additional costs for companies. ...
The warehousing sector is among the top when it comes to the risk of developing work-related musculoskeletal disorders (WMSDs), in particular low back pain (LBP). In this sector, LBP is a prevalent issue, due to the nature of the job of lifting and moving (heavy) objects around. The issue has significant implications for the workers’ health, in terms of quality of life. Companies and society feel the consequences in terms of financial costs. This issue could be tackled by introducing smart technology in the form of a smart safety shoe. The concept has been developed by a strategic product design student and the strategic direction has been determined. This project explores the concept further and validates the idea of smart safety shoes to reduce the risk of LBP during manual handling, through technological means.
To understand the problem of LBP in context, extensive literature research was conducted on ergonomics. Understanding what causes it and the current methods to reduce the risks. Further, looking into the possibility of detecting causes through technology. The research results were used to build a prototype for validation of the concept.
The causality of LBP is not easy to point out, as multiple factors (physical, psychosocial, and individual) play a role in its development. Research does conclude that physical factors play a major role, which is related to heavy lifting, repetitiveness, and awkward postures. Manual handling can be performed safely as long as the weight is below 23 kg and correct postures are adopted. Though not all workers adhere to correct posture, and it is hard to track through observational methods.
Postures can be tracked or detected through plantar pressure distribution (PPD), by using pressure sensors. These sensors can be placed within safety shoes and will collect PPD data of workers. The PPD data shows certain patterns and have characteristics that can be linked to different postures. The data can be analysed using machine learning, to automate the process and could be able to give feedback to the user when a risky posture is adopted.
A pressure insole has been prototyped with the conducted research to collect PPD data of different postures (stoop lifting, lifting above shoulder height, and asymmetrical lifting). The collected data were manually analysed to understand how patterns may look like. A machine learning model was made, using a tree algorithm, to analyse the data as well. It can classify all the measured static postures with 100% accuracy. Dynamic lifting data were not analysed by the model yet as it needs additional data preparation. At this point, the concept needs more development to analyse dynamic data and to implement the hardware in the safety shoes.
Based on the results, the core components of the concept have been proven to work and able to detect different postures with great accuracy. The idea of a smart safety shoe that can detect and warn the worker of potential injury is not far-fetched.
This project is the first step in the development of the concept. Due to the complexity of the issue and required knowledge, additional research is needed for the continuation of the project. The posture database has to be set up, improving the machine learning model for dynamic lifting data, hardware design and a live feedback system. With these developments, a smart safety shoe could be brought to market that could improve workers' lives and save additional costs for companies.
To understand the problem of LBP in context, extensive literature research was conducted on ergonomics. Understanding what causes it and the current methods to reduce the risks. Further, looking into the possibility of detecting causes through technology. The research results were used to build a prototype for validation of the concept.
The causality of LBP is not easy to point out, as multiple factors (physical, psychosocial, and individual) play a role in its development. Research does conclude that physical factors play a major role, which is related to heavy lifting, repetitiveness, and awkward postures. Manual handling can be performed safely as long as the weight is below 23 kg and correct postures are adopted. Though not all workers adhere to correct posture, and it is hard to track through observational methods.
Postures can be tracked or detected through plantar pressure distribution (PPD), by using pressure sensors. These sensors can be placed within safety shoes and will collect PPD data of workers. The PPD data shows certain patterns and have characteristics that can be linked to different postures. The data can be analysed using machine learning, to automate the process and could be able to give feedback to the user when a risky posture is adopted.
A pressure insole has been prototyped with the conducted research to collect PPD data of different postures (stoop lifting, lifting above shoulder height, and asymmetrical lifting). The collected data were manually analysed to understand how patterns may look like. A machine learning model was made, using a tree algorithm, to analyse the data as well. It can classify all the measured static postures with 100% accuracy. Dynamic lifting data were not analysed by the model yet as it needs additional data preparation. At this point, the concept needs more development to analyse dynamic data and to implement the hardware in the safety shoes.
Based on the results, the core components of the concept have been proven to work and able to detect different postures with great accuracy. The idea of a smart safety shoe that can detect and warn the worker of potential injury is not far-fetched.
This project is the first step in the development of the concept. Due to the complexity of the issue and required knowledge, additional research is needed for the continuation of the project. The posture database has to be set up, improving the machine learning model for dynamic lifting data, hardware design and a live feedback system. With these developments, a smart safety shoe could be brought to market that could improve workers' lives and save additional costs for companies.
Master thesis
(2020)
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Eric Wolters, Frans van der Helm, Jinne Geelen, Anton Jellema, Peter Desain, Zachary Freudenburg
Patients suffering from diseases affecting verbal communication can make use of assistive devices to improve communication. Some severely disabled patients can only produce yes-or-no responses to communicate. These responses can be created through a physical switch, eye blink, or a 'mental' click created by brain activity. The yes-or-no responses can be used to communicate by making multiple selections between two groups of letters. Through deduction paradigms the target letter can be determined. Current assistive devices use a Row Column or Huffman paradigm to communicate. Communication rates achieved with these paradigms are slow compared to regular conversation rates and to assistive devices using eye-tracking. Furthermore, these deduction paradigms have only been tested in assistive devices with no or little noise. Noise affects the yes-or-no responses and leads to the selection of incorrect letters. There are assistive devices that suffer from high noise levels which affect communication rates. This work evaluates four communication paradigms for a range of noise conditions to improve communication rates. Row Column, Huffman, and two novel paradigms are evaluated. The two novel paradigms, based on Variable-Length Error-Correcting code and Weighted Huffman encoding, are designed for environments with noise. Evaluation of these paradigms is done through simulation and human experiments. A mathematical model is developed for simulation, and an emulator emulating an assistive device is used for human experiments. Spelling speed and cognitive effort are used as performance measures. The simulations were shown to be useful as a tool for predicting the relative performance of the paradigms in real use situations. Results from the simulation and experiments found that the effect of noise is paradigm dependent and should be taken into consideration. A novel paradigm was shown to be optimal for selective noise conditions. Row Column scanning scored the best on cognitive effort, while Huffman encoding resulted in the fastest typing speed in almost all noise conditions. Through emulation and simulation, Huffman encoding is validated as the optimal paradigm to increase communication rates. The mathematical model set a basis on which more research into optimal communication paradigms for discrete control assistive devices can be conducted.
...
Patients suffering from diseases affecting verbal communication can make use of assistive devices to improve communication. Some severely disabled patients can only produce yes-or-no responses to communicate. These responses can be created through a physical switch, eye blink, or a 'mental' click created by brain activity. The yes-or-no responses can be used to communicate by making multiple selections between two groups of letters. Through deduction paradigms the target letter can be determined. Current assistive devices use a Row Column or Huffman paradigm to communicate. Communication rates achieved with these paradigms are slow compared to regular conversation rates and to assistive devices using eye-tracking. Furthermore, these deduction paradigms have only been tested in assistive devices with no or little noise. Noise affects the yes-or-no responses and leads to the selection of incorrect letters. There are assistive devices that suffer from high noise levels which affect communication rates. This work evaluates four communication paradigms for a range of noise conditions to improve communication rates. Row Column, Huffman, and two novel paradigms are evaluated. The two novel paradigms, based on Variable-Length Error-Correcting code and Weighted Huffman encoding, are designed for environments with noise. Evaluation of these paradigms is done through simulation and human experiments. A mathematical model is developed for simulation, and an emulator emulating an assistive device is used for human experiments. Spelling speed and cognitive effort are used as performance measures. The simulations were shown to be useful as a tool for predicting the relative performance of the paradigms in real use situations. Results from the simulation and experiments found that the effect of noise is paradigm dependent and should be taken into consideration. A novel paradigm was shown to be optimal for selective noise conditions. Row Column scanning scored the best on cognitive effort, while Huffman encoding resulted in the fastest typing speed in almost all noise conditions. Through emulation and simulation, Huffman encoding is validated as the optimal paradigm to increase communication rates. The mathematical model set a basis on which more research into optimal communication paradigms for discrete control assistive devices can be conducted.
Falls in the elderly are a leading cause of injury, affecting one in three older adults annually. These fall incidents can lead to various disabling conditions, and therefore have the ability to affect one’s quality of life and independence. Not only are falls potentially taxing to the individual, they are also responsible for a big portion of annual health care costs. Due to an ageing society, the number of falls and their consequences will grow in parallel with the expanding number of seniors, becoming an even greater concern for the health care system. Therefore, there is an ever-increasing need to develop (cost-)effective fall prediction systems to reduce these financial and physical burdens associated with the consequences of a fall. Introducing the design proposal of my graduation thesis: smart insoles with accessory mobile application, the ‘StApp’. The insoles with an integrated fall prediction smart system capture the physiological risk factor of an impaired minimum toe clearance (MTC) variable, signal the impending danger to the user, and hence, aid falls prevention in the elderly. The final product consists of three segments, detect - warn - and inform, represented in the two separate products. (Detect) Smart insoles that analyse and monitor the user’s gait in real-time, in particular the MTC parameter, through a sensing technology integrated in the sole. (Warn) When MTC values display an apparent risk, the user is alerted through a technological intervention. This presents itself in the form of vibrational stimulus, embedded in the support arch of the smart insole. Hereby, the whole smart system, including the intervention, is embedded in the smart insole, discreetly concealed. (Inform) For the sensor data to be meaningful to the user, an accessory mobile application monitoring the MTC- and multiple other gait parameters is suggested. The StApp presents concrete information and advice on sufficient and safe exercise to improve the user’s MTC and overall gait and balance. An experimental research study was conducted to preliminarily validate the viability of the main product-idea of the smart insoles, studying the effect of the product’s intervention. A minimum of 2 minutes of treadmill walking was analysed for two young adults (1 M, 1 F) using the Tracker motion analysis software. The effect of the intervention was clearly illustrated in the data gathered in this pilot test, as the effect of the intervention deemed to be statistically for all administered vibrational stimuli. It seems to be an appropriate tool to optimize the toe clearance parameters in the pursuit for strategies of falls prevention. However, further in-depth research is required to explore the intervention’s characteristics and study the effect of the intervention on the elderly’s gait. Finally, as the wearable technology depicted enables optimization of elderly care, healthcare professionals who might be interested in giving more personalized advice to their patients will benefit from the design of the smart insole and accessory StApp, presented in this project.
...
Falls in the elderly are a leading cause of injury, affecting one in three older adults annually. These fall incidents can lead to various disabling conditions, and therefore have the ability to affect one’s quality of life and independence. Not only are falls potentially taxing to the individual, they are also responsible for a big portion of annual health care costs. Due to an ageing society, the number of falls and their consequences will grow in parallel with the expanding number of seniors, becoming an even greater concern for the health care system. Therefore, there is an ever-increasing need to develop (cost-)effective fall prediction systems to reduce these financial and physical burdens associated with the consequences of a fall. Introducing the design proposal of my graduation thesis: smart insoles with accessory mobile application, the ‘StApp’. The insoles with an integrated fall prediction smart system capture the physiological risk factor of an impaired minimum toe clearance (MTC) variable, signal the impending danger to the user, and hence, aid falls prevention in the elderly. The final product consists of three segments, detect - warn - and inform, represented in the two separate products. (Detect) Smart insoles that analyse and monitor the user’s gait in real-time, in particular the MTC parameter, through a sensing technology integrated in the sole. (Warn) When MTC values display an apparent risk, the user is alerted through a technological intervention. This presents itself in the form of vibrational stimulus, embedded in the support arch of the smart insole. Hereby, the whole smart system, including the intervention, is embedded in the smart insole, discreetly concealed. (Inform) For the sensor data to be meaningful to the user, an accessory mobile application monitoring the MTC- and multiple other gait parameters is suggested. The StApp presents concrete information and advice on sufficient and safe exercise to improve the user’s MTC and overall gait and balance. An experimental research study was conducted to preliminarily validate the viability of the main product-idea of the smart insoles, studying the effect of the product’s intervention. A minimum of 2 minutes of treadmill walking was analysed for two young adults (1 M, 1 F) using the Tracker motion analysis software. The effect of the intervention was clearly illustrated in the data gathered in this pilot test, as the effect of the intervention deemed to be statistically for all administered vibrational stimuli. It seems to be an appropriate tool to optimize the toe clearance parameters in the pursuit for strategies of falls prevention. However, further in-depth research is required to explore the intervention’s characteristics and study the effect of the intervention on the elderly’s gait. Finally, as the wearable technology depicted enables optimization of elderly care, healthcare professionals who might be interested in giving more personalized advice to their patients will benefit from the design of the smart insole and accessory StApp, presented in this project.
Master thesis
(2019)
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Stijn Jagers op Akkerhuis, Wilhelm Frederik van der Vegte, Anton Jellema, IJsbrand de Lange
This report presents a design proposal for a product that will suppress the tremor of patients diagnosed with Essential Tremor (ET). People suffering from ET are restricted in their ability to function in everyday life, due to a constraint of performing delicate movements. Simple tasks, such as drinking and eating are a great challenge for individuals diagnosed with ET.
STIL B.V. works on the development of an alternative solution to dampen a forearm tremor. STIL B.V. is developing a product that dampens the tremor by actively counteracting the movement of its users. With this, the product offers tremor patients a solution that does not involve surgery or use of medication.
The project focuses on finding improvements for the STIL product by developing a solution for recently diagnosed ET patients with an invalidating forearm tremor. The final goal was to create a product that would improve the life quality of its users, by giving individuals with ET back control over their arms. ET patients often mentioned that it is difficult to be in a group or participate in a social activity. Awkward situations occur frequently, making them socially shy. The objective was to help patients regain social confidence by making use of the product.
The final product proposal exists of two parts, a brace and an active dampening element (Exshell). The brace is used to connect the Exshell to the arm. The Exshell contains an active dampening element to stabilize the arm. At the start of this project, the development of the brace, the part that has contact with the skin, was not yet started. A simple elastic band combined with a coarse vibration measurement principle was used for the prototypes.
An efficient attachment method to the users arm and a connection to the Exshell have been designed, made and tested. Additionally a set of different brace sizes has been developed to create a comfortable design for an as large as possible target group.
To stimulate the use of the product, a brace has been designed that is as comfortable as possible. This has been done by making an optimized ergonomic design for ET patients. The brace can be worn all day by the user and when needed the Exshell can be slid over the wrist and actively counteract forearm tremors.
An ergonomic test on healthy individuals has been conducted in order to discover the fit of the different developed brace sizes. The used scaling method for different sizes proved to be effective and by offering five different sizes a comfortable fit can be offered to almost everyone.
The usability and functionality of the brace design has been validated during a patient test. The test showed that the brace is easy to use for tremor patients.
The final design result presents a proposal of how the future product of STIL BV. might look like. The results from the analysis and validation phase have been combined and a future vision of the products embodiment is presented. ...
STIL B.V. works on the development of an alternative solution to dampen a forearm tremor. STIL B.V. is developing a product that dampens the tremor by actively counteracting the movement of its users. With this, the product offers tremor patients a solution that does not involve surgery or use of medication.
The project focuses on finding improvements for the STIL product by developing a solution for recently diagnosed ET patients with an invalidating forearm tremor. The final goal was to create a product that would improve the life quality of its users, by giving individuals with ET back control over their arms. ET patients often mentioned that it is difficult to be in a group or participate in a social activity. Awkward situations occur frequently, making them socially shy. The objective was to help patients regain social confidence by making use of the product.
The final product proposal exists of two parts, a brace and an active dampening element (Exshell). The brace is used to connect the Exshell to the arm. The Exshell contains an active dampening element to stabilize the arm. At the start of this project, the development of the brace, the part that has contact with the skin, was not yet started. A simple elastic band combined with a coarse vibration measurement principle was used for the prototypes.
An efficient attachment method to the users arm and a connection to the Exshell have been designed, made and tested. Additionally a set of different brace sizes has been developed to create a comfortable design for an as large as possible target group.
To stimulate the use of the product, a brace has been designed that is as comfortable as possible. This has been done by making an optimized ergonomic design for ET patients. The brace can be worn all day by the user and when needed the Exshell can be slid over the wrist and actively counteract forearm tremors.
An ergonomic test on healthy individuals has been conducted in order to discover the fit of the different developed brace sizes. The used scaling method for different sizes proved to be effective and by offering five different sizes a comfortable fit can be offered to almost everyone.
The usability and functionality of the brace design has been validated during a patient test. The test showed that the brace is easy to use for tremor patients.
The final design result presents a proposal of how the future product of STIL BV. might look like. The results from the analysis and validation phase have been combined and a future vision of the products embodiment is presented. ...
This report presents a design proposal for a product that will suppress the tremor of patients diagnosed with Essential Tremor (ET). People suffering from ET are restricted in their ability to function in everyday life, due to a constraint of performing delicate movements. Simple tasks, such as drinking and eating are a great challenge for individuals diagnosed with ET.
STIL B.V. works on the development of an alternative solution to dampen a forearm tremor. STIL B.V. is developing a product that dampens the tremor by actively counteracting the movement of its users. With this, the product offers tremor patients a solution that does not involve surgery or use of medication.
The project focuses on finding improvements for the STIL product by developing a solution for recently diagnosed ET patients with an invalidating forearm tremor. The final goal was to create a product that would improve the life quality of its users, by giving individuals with ET back control over their arms. ET patients often mentioned that it is difficult to be in a group or participate in a social activity. Awkward situations occur frequently, making them socially shy. The objective was to help patients regain social confidence by making use of the product.
The final product proposal exists of two parts, a brace and an active dampening element (Exshell). The brace is used to connect the Exshell to the arm. The Exshell contains an active dampening element to stabilize the arm. At the start of this project, the development of the brace, the part that has contact with the skin, was not yet started. A simple elastic band combined with a coarse vibration measurement principle was used for the prototypes.
An efficient attachment method to the users arm and a connection to the Exshell have been designed, made and tested. Additionally a set of different brace sizes has been developed to create a comfortable design for an as large as possible target group.
To stimulate the use of the product, a brace has been designed that is as comfortable as possible. This has been done by making an optimized ergonomic design for ET patients. The brace can be worn all day by the user and when needed the Exshell can be slid over the wrist and actively counteract forearm tremors.
An ergonomic test on healthy individuals has been conducted in order to discover the fit of the different developed brace sizes. The used scaling method for different sizes proved to be effective and by offering five different sizes a comfortable fit can be offered to almost everyone.
The usability and functionality of the brace design has been validated during a patient test. The test showed that the brace is easy to use for tremor patients.
The final design result presents a proposal of how the future product of STIL BV. might look like. The results from the analysis and validation phase have been combined and a future vision of the products embodiment is presented.
STIL B.V. works on the development of an alternative solution to dampen a forearm tremor. STIL B.V. is developing a product that dampens the tremor by actively counteracting the movement of its users. With this, the product offers tremor patients a solution that does not involve surgery or use of medication.
The project focuses on finding improvements for the STIL product by developing a solution for recently diagnosed ET patients with an invalidating forearm tremor. The final goal was to create a product that would improve the life quality of its users, by giving individuals with ET back control over their arms. ET patients often mentioned that it is difficult to be in a group or participate in a social activity. Awkward situations occur frequently, making them socially shy. The objective was to help patients regain social confidence by making use of the product.
The final product proposal exists of two parts, a brace and an active dampening element (Exshell). The brace is used to connect the Exshell to the arm. The Exshell contains an active dampening element to stabilize the arm. At the start of this project, the development of the brace, the part that has contact with the skin, was not yet started. A simple elastic band combined with a coarse vibration measurement principle was used for the prototypes.
An efficient attachment method to the users arm and a connection to the Exshell have been designed, made and tested. Additionally a set of different brace sizes has been developed to create a comfortable design for an as large as possible target group.
To stimulate the use of the product, a brace has been designed that is as comfortable as possible. This has been done by making an optimized ergonomic design for ET patients. The brace can be worn all day by the user and when needed the Exshell can be slid over the wrist and actively counteract forearm tremors.
An ergonomic test on healthy individuals has been conducted in order to discover the fit of the different developed brace sizes. The used scaling method for different sizes proved to be effective and by offering five different sizes a comfortable fit can be offered to almost everyone.
The usability and functionality of the brace design has been validated during a patient test. The test showed that the brace is easy to use for tremor patients.
The final design result presents a proposal of how the future product of STIL BV. might look like. The results from the analysis and validation phase have been combined and a future vision of the products embodiment is presented.
This graduation report describes the development of a personalised and customised knitwear experience for the company STRIKKS. The goal was to design an interactive experience that will sell personalised knitwear in a retail environment. In this experience an accurate display of the garment should give the customer insights into how the garment will look on their body and will enable them to make decisions that will lead to a satisfied result. The experience should convince the customer of purchasing the garment but should also avoid disappointment after trying the garment on the first time. This concept was validated using a user test. 6 Participants used the garment visualisation to create their own unique sweaters which have been produced by STRIKKS. Comparing the visualisation and knitted sweaters confirmed the value that is being added with a visualisation. Based on this test conclusions were drawn and final recommendations were given to STRIKKS for further development of the concept.
...
This graduation report describes the development of a personalised and customised knitwear experience for the company STRIKKS. The goal was to design an interactive experience that will sell personalised knitwear in a retail environment. In this experience an accurate display of the garment should give the customer insights into how the garment will look on their body and will enable them to make decisions that will lead to a satisfied result. The experience should convince the customer of purchasing the garment but should also avoid disappointment after trying the garment on the first time. This concept was validated using a user test. 6 Participants used the garment visualisation to create their own unique sweaters which have been produced by STRIKKS. Comparing the visualisation and knitted sweaters confirmed the value that is being added with a visualisation. Based on this test conclusions were drawn and final recommendations were given to STRIKKS for further development of the concept.