Are consumers satisfied with the use of prosthetic sports feet and the provision process? A mixed-methods study

Poonsiri, Jutamanee; Putten, S.W.E. van; Ausma, A.T.; Geertzen, Jan H. B.; Dijkstra, Pieter U.; Dekker, Rienk

doi:10.1016/j.mehy.2020.109869

Cited by 8 publications

(15 citation statements)

References 25 publications

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“…So, based on fuzzy algorithm, this study studies images with great changes in the motion and posture of the target object, which will help for us to realize sports images [6].…”

Section: Introductionmentioning

confidence: 99%

Deep Learning Algorithm in Biomedical Engineering in Intelligent Automatic Processing and Analysis of Sports Images

Bao

Bei

Xiang

et al. 2022

Wireless Communications and Mobile Computing

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In order to improve the detection and identification ability of sports injury ultrasound medicine, a segmentation method of sports injury ultrasound medical image based on local features is proposed, and the research on the sports injury ultrasound medical detection and identification ability is carried out. Methods of the sports injury ultrasound medical image segmentation model are established; the sports injury ultrasound medical image information is enhanced by using the sports skeletal muscle block matching technology; the image features are extracted; and the characteristics of sports injury ultrasound medical images are analyzed by CT bright spot feature transmission. In detail, combined with the deep convolutional neural network training method, the extracted sports injury points are automatically detected for sports injury ultrasound medical images, and the sports injury ultrasound medical image segmentation is realized. The simulation results show that this method has high accuracy for sports injury ultrasound medical image segmentation, the error value can be controlled below 0.103, and finally, the effect of zero error is achieved. It is confirmed that the method proposed in this paper has high resolution and accuracy for sports injury point detection and has strong practical application ability.

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“…So, based on fuzzy algorithm, this study studies images with great changes in the motion and posture of the target object, which will help for us to realize sports images [6].…”

Section: Introductionmentioning

confidence: 99%

Deep Learning Algorithm in Biomedical Engineering in Intelligent Automatic Processing and Analysis of Sports Images

Bao

Bei

Xiang

et al. 2022

Wireless Communications and Mobile Computing

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“…An additional third subtheme now describes the importance of a prosthesis which enables participation. The function of prosthetic components and how they enable people to participate was described in 18 studies [13,35,[60][61][62][63]65,66,71,72,36,[41][42][43]48,52,55,57]. Participants described wanting a leg that was waterproof so they could go fishing, or a flexible ankle so they could lift objects at work.…”

Section: Domain 1 -I Am Able To Participate In My Important Activitie...mentioning

confidence: 99%

“…However, clothing also appeared to contribute to concerns, especially in certain social situations [46,61,62,75,77]. Other facilitators of acceptance, concerning both appearance and function, were described as a positive problem-solving attitude [13,41,49,53,55,56,58,62,63,65,66,70,74], being able to participate in important activities and roles [42,[44][45][46]51,64,70,71,76], time since amputation [62], spirituality [40,53,63,71] and peer support [13,[40][41][42][44][45][46]50,54,58,67,76,77]. Participants in 9 of the included studies highlighted concerns about the impact amputation and prosthesis use would have on their health and wellbeing throughout their life course [36,…”

Section: Domain 5 -I Am Able To Accept My New Normalmentioning

confidence: 99%

Development of the ECLIPSE model of meaningful outcome domains following lower limb amputation and prosthetic rehabilitation, through systematic review and best fit framework synthesis

Ostler,

Dickinson,

Metcalf

et al. 2024

Preprint

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Background Little is known about which outcome domains characterise meaningful recovery following prosthetic rehabilitation and should be measured. Our previous qualitative work developed a conceptual model of outcome domains which are meaningful to patients. This qualitative synthesis aims to develop that model by exploring views and experiences of recovery captured in the limb loss literature, and use these to produce a second iteration of the model describing outcome domains of importance following prosthetic rehabilitation from the patient's perspective. Methods Systematic searches were conducted using CINAHL, Psychinfo and Web of Science from 2011 to early 2023. Studies with a qualitative design focusing on views and experiences of lower limb prosthetic users were eligible for inclusion. Quality was assessed using the CASP tool. 'Best Fit' framework synthesis was used to synthesise the evidence and develop the conceptual model. Results 40 studies were included, describing the experiences of 539 participants. Data supported the pre-existing conceptual model and led to development of four of the five domains. The newly named ECLIPSE model describes meaningful outcome domains as 1) Being able to participate in important activities and roles, 2) Participating in the way I want to, 3) My prosthesis works for me, 4) If I am in pain, I can manage it, and 5) I am able to accept my new normal. Studies came from 15 countries showing good coverage of high-income settings. Few participants from low-and-middle-income countries were included, it is unclear if the ECLIPSE model describes outcome domains of importance in these settings. Conclusions This synthesis provides a rigorous foundation for understanding outcome domains of importance following lower limb prosthetic rehabilitation from the patient's perspective. The ECLIPSE model is an accessible representation of recovery which could direct rehabilitation programmes, as well as inform the evaluation of prosthetic care through the selection of outcome measures.

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“…Scholars put forward their own suggestions from various angles. For example, Poonsiri et al [6] proposed that to change the problem of talent training for volleyball reserve personnel in my country, it is necessary to give full play to the collaborative effect of sports and education departments, give full play to the commercial value of volleyball, and develop the market potential of volleyball, so as to attract more young people to participate in volleyball. Recently, Gayman and Eys [7] and others believe that to improve the training efficiency of volleyball reserve talents, it is necessary to innovate in relevant systems, strengthen the role of the market in the development of volleyball, and, at the same time, properly improve the introduction system of volleyball reserve talents.…”

Section: Research On the Training And Reserve Of High-levelmentioning

confidence: 99%

Application of Improved $K$ -Means Clustering Algorithm in Targeted Practice of College Volleyball Fitness Training Classification

Feng

2022

Wireless Communications and Mobile Computing

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The high-level men’s volleyball team in ordinary colleges and universities is an important place for the country to cultivate outstanding volleyball reserve talents. Especially under the background of “integration of sports and education,” the status of high-level men’s volleyball teams in ordinary colleges and universities in my country’s volleyball career has been further improved. In affirmation and attention, routine training is an important part of the work of high-level men’s volleyball teams in ordinary colleges and universities. Cultivating high-level and high-quality outstanding volleyball reserve talents is an important goal of high-level men’s volleyball teams in ordinary colleges and universities. The growth of high-level men’s volleyball players requires high quality. For training support, in order to improve the training quality of the men’s volleyball team at the general college level, it is necessary to evaluate the training quality of the existing high-level sports teams. In order to achieve “different from person to person” and “teaching according to aptitude” college students’ volleyball training behavior prediction and guidance content recommendation, and to achieve a classification promotion strategy, this research uses the K -means clustering algorithm and PCA-GS-SVM algorithm to train college students’ volleyball training, adhering to behavior. The data classifier has high training efficiency, and the accuracy rate is higher than 87% in both the training set and the test set, which can meet the application requirements of college students’ volleyball training adhere to the classification and promotion strategy of behavior information platform and effectively support the practical application of the model. The volleyball training adherence behaviors are divided into eight categories, and specific classification promotion strategies are formulated according to the characteristics of different categories of behaviors.

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Are consumers satisfied with the use of prosthetic sports feet and the provision process? A mixed-methods study

Cited by 8 publications

References 25 publications

Deep Learning Algorithm in Biomedical Engineering in Intelligent Automatic Processing and Analysis of Sports Images

Deep Learning Algorithm in Biomedical Engineering in Intelligent Automatic Processing and Analysis of Sports Images

Development of the ECLIPSE model of meaningful outcome domains following lower limb amputation and prosthetic rehabilitation, through systematic review and best fit framework synthesis

Application of Improved $K$ -Means Clustering Algorithm in Targeted Practice of College Volleyball Fitness Training Classification

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Are consumers satisfied with the use of prosthetic sports feet and the provision process? A mixed-methods study

Cited by 8 publications

References 25 publications

Deep Learning Algorithm in Biomedical Engineering in Intelligent Automatic Processing and Analysis of Sports Images

Deep Learning Algorithm in Biomedical Engineering in Intelligent Automatic Processing and Analysis of Sports Images

Development of the ECLIPSE model of meaningful outcome domains following lower limb amputation and prosthetic rehabilitation, through systematic review and best fit framework synthesis

Application of Improved K -Means Clustering Algorithm in Targeted Practice of College Volleyball Fitness Training Classification

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Product

Resources

About

Application of Improved $K$ -Means Clustering Algorithm in Targeted Practice of College Volleyball Fitness Training Classification