Development of a Mobile App for Objective Assessment of Prosthesis Rejection Rates in End-Users

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dc.contributor.authorVinjamuri, Ramana
dc.date.accessioned2022-10-07T13:59:12Z
dc.date.available2022-10-07T13:59:12Z
dc.date.issued2022
dc.descriptionRESNA Annual Conference - 2022
dc.description.abstractAccording to the World Health Organization, there are over 30 million prosthesis users worldwide, with upper limb prostheses being especially common. In 2005, nearly 541,000 Americans suffered from upper limb loss [14]. As the number of upper limb loss cases is expected to double by 2050, there is an urgent need for functional and easy-to-use prostheses; however, to do so, providers must make significant efforts to identify potential sources of dissatisfaction and accurate estimates of rejection rates. In 1986, rejection rates upwards of 80% were present in body-powered hands [3], and, although reported prosthetic rejection rates have decreased with modern technology, over 30% of pediatric prosthetic users and 20% of adults are still unsatisfied with body-powered and electric prosthetics, respectively [12]. Rejection rates are frequently measured via questionnaires or surveys, such as European Quality of Life Five Dimension (EQ-5D), which often hold potential biases. Relying on these necessary but limited assessments over the past 25 years, researchers have found high prosthetic rejection rates. On the other hand, a more recent study examined prosthesis use and abandonment among prosthesis users with upper limb deficiencies in the US and Japan and concluded that many researchers published exaggerated results from their surveying methods. They determined that there is a 9% rejection rate, and 70% of users use their prostheses daily [12]. In this paper, we propose an objective assessment of rejection rates, through smart wearables and neuromarketing approaches, while generating a user-friendly training smartphone app. Novel neuromarketing approaches, including electroencephalography (EEG) and electrodermal activity (EDA), have been used for attention deficit hyper disorder (ADHD) diagnosis, substance use disorders (SUD), biofeedback, and direct control of prosthesis, but have not been used to measure the end user satisfaction. Currently, many upper limb prosthesis users are unsatisfied with the functionality, comfort, and training received for their prosthesis. In this paper, we propose a smartphone app to improve usability by balancing functionality and aesthetics. We aim to gather data from patients with two goals in mind: engagement (how long the patient is spending to learn about how their prosthetic works) and growth (the patient's progression in their engagement and overall satisfaction with the machine). Using persuasive technology and positive intermittent reinforcement, (ex. watching and posting success stories) we hope to lower prosthetic rejection rates by creating a more comfortable, user-friendly experience. filler Figure 1. By using a combination of EEG and EDA, we plan to measure the current prosthesis satisfaction rates. Then, we can compare this with the patients' satisfaction after using our training app. Through this procedure, we can get 1) unbiased reports of prosthetic rejection and 2) accurate accounts of our app's success. Providers frequently expect prosthesis users to use their machines daily. Nonetheless, our team also acknowledged the need for reminders and how they impact learning ability. We can manipulate and amplify the effects of the implementation of daily successes through the ACT-R (Adaptive Control of Thought Rational) theory, which proves that the effects of reminders vary based on frequency.en_US
dc.description.sponsorshipThis work was supported in part by the National Science Foundation. Grant No# NSF CAREER Award HCC-XXXXX.en_US
dc.description.urihttps://www.resna.org/sites/default/files/conference/2022/AccessAndAccommodations/121_Vinjamuri.htmlen_US
dc.genreconference papers and proceedingsen_US
dc.identifierdoi:10.13016/m23y8h-4oas
dc.identifier.citationVinjamuri, Ramana. Development of a Mobile App for Objective Assessment of Prosthesis Rejection Rates in End-Users. RESNA Annual Conference 2022. https://www.resna.org/sites/default/files/conference/2022/AccessAndAccommodations/121_Vinjamuri.htmlen_US
dc.identifier.urihttp://hdl.handle.net/11603/26110
dc.language.isoen_USen_US
dc.publisherRESNA Annual Conferenceen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.en_US
dc.subjectprosthesis rejection ratesen_US
dc.subjectprosthesis satisfaction ratesen_US
dc.subjectprosthesis user training appen_US
dc.subjectEEGen_US
dc.subjecttranscranial magnetic stimulation (TMS)en_US
dc.titleDevelopment of a Mobile App for Objective Assessment of Prosthesis Rejection Rates in End-Usersen_US
dc.typeTexten_US

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