Cloud Computing Mobile Application for Remote Monitoring of Bell’s Palsy

Watts, Paul; Breedon, Philip; Nduka, Charles; Neville, Catriona; Venables, Vanessa; Clarke, Siobhán

doi:10.1007/s10916-020-01605-7

Cited by 11 publications

(8 citation statements)

References 14 publications

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“…As the present therapy is dependent on the surveillance of a trained therapy, it will also be of interest to develop a remote rehabilitation concept. Therefore, we will need remote EMG devices and especially a simplification of the camera technology using conventional smart phones or, for instance, special remote activity eye wear ( 39 , 40 ).…”

Section: Discussionmentioning

confidence: 99%

Effect of an Intensified Combined Electromyography and Visual Feedback Training on Facial Grading in Patients With Post-paralytic Facial Synkinesis

Volk

Roediger

Geißler

et al. 2021

Front. Rehabilit. Sci.

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Background: There is no current standard for facial synkinesis rehabilitation programs. The benefit and stability of effect of an intensified 10-day facial training combining electromyography and visual biofeedback training was evaluated.Methods: Fifty-four patients (77.8% female; median age: 49.5 years) with post-paralytic facial synkinesis (median time to onset of paralysis: 31.1 months) were included in retrospective longitudinal study between January 2013 and June 2016. Facial function was assesses at baseline (T0), first days of training (T1), last day of training (T2), and follow-up visit (T3) at a median time of 6 months later using the House-Brackmann (HB) facial nerve grading system, Stennert index (SI), Facial Nerve Grading System 2.0 (FNGS 2.0), and Sunnybrook Facial Grading System (SFGS). Pairwise comparisons between the time points with post-hoc Bonferroni correction were performed.Results: No significant changes of the gradings and subscores were seen between T0 and T1 (all p > 0.01). The 10-day combined and intensified feedback training between T1 and T2 improved facial symmetry and decreased synkinetic activity. Facial grading with the FNGS 2.0 or the SFGS were most suited to depict the training effect. FNGS 2.0, regional score, FNGS 2.0, synkinesis score, and FNGS 2.0 total score improved significantly (all p ≤ 0.0001). Both, the FNGS 2.0 and the SFGS showed the strongest improvement in the nasolabial fold/zygomatic and the oral region. Neither the age of the patient (r = 0.168; p = 0.224), the gender (r = 0.126; p = 0.363) nor the length of the interval between onset of the palsy and training start (r = 0.011; p = 0.886) correlated with the changes of the SFGS between T1 and T2. The results remained stable between T2 and T3 without any further significant change.Conclusion: Intensified daily combined electromyography and visual biofeedback training over 10 days was effective in patients with facial synkinesis and benefits were stable 6 months after therapy.

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Section: Discussionmentioning

confidence: 99%

Effect of an Intensified Combined Electromyography and Visual Feedback Training on Facial Grading in Patients With Post-paralytic Facial Synkinesis

Volk

Roediger

Geißler

et al. 2021

Front. Rehabilit. Sci.

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“…The expressed interest in continual rehabilitation, especially in patients with prior experience with facial therapy with a therapist, higher physical burden, especially dysfunctional eye closure, make clear that new and additional therapy concepts have to be developed for a continual facial therapy. A possible solution could be the development and validation of home-based sensor-based digital technology at best in combination with a remote monitoring function for the involved therapist [ 11 , 12 , 34 ]. The subgroup of the patients with high psychosocial burden would probably profit from an integration of remotely communicated, therapist-delivered psychotherapy [ 35 ].…”

Section: Discussionmentioning

confidence: 99%

Continual rehabilitation motivation of patients with postparalytic facial nerve syndrome

Osthues

Kuttenreich

Volk

et al. 2021

Eur Arch Otorhinolaryngol

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Purpose To evaluate the continued rehabilitation motivation in patients with postparalytic facial synkinesis (PFS). Methods In this single-center cross-sectional survey, the multidimensional patient questionnaire for assessment of rehabilitation motivation (PAREMO-20) was used to assess the rehabilitation motivation. Associations Sunnybrook and Stennert index grading, Facial Clinimetric Evaluation (FaCE) survey, general quality of life (SF-36), Liebowitz Social Anxiety Scale (LSAS), Patient Health Questionnaire (PHQ)-9, technology commitment and affinity, and interest in further therapy were analyzed. Results 69 adults with PFS (73% women; median age: 54 years) answered the survey. In comparison to prior treatment forms, there was a significant higher future interest in computer-based home facial training (p < 0.0001). For PAREMO Psychological burden subscore, SF36 Emotional role was the highest negative correlative factor (p < 0.0001). For PAREMO Physical burden subscore, SF-36 General health was the highest negative correlative factor (p = 0.018). Working (p = 0.033) and permanent relationship (p = 0.029) were the only independent factors correlated to PAREMO Social Support Subscore. Higher positive impacts of technology affinity was inversely correlated to PAREMO Knowledge subscore (p = 0.017). Lower SF-36 Role physical subscore p = 0.045) and a lower SF-36 General health (p = 0.013) were correlated to a higher PAREMO Skepticism subscore. Conclusions Patients with PFS seem to have a high facial motor and non-motor psychosocial impairment even after several facial therapies. Rehabilitation-related motivation increases with both, higher facial motor and non-motor dysfunction. Social and emotional dysfunction are drivers to be interested in innovative digital therapy forms.

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“…In addition, this task does not need additional device costs. The patients can receive various health services from the mobile device they are already accustomed to [25].…”

Section: Mobile Applications For Identification Of Skin Lesion Imagesmentioning

confidence: 99%

“…There are variety of mobile applications to improve healthcare [25][26][27][28]. Some of them are developed for identification of skin lesions.…”

Section: Mobile Applications For Identification Of Skin Lesion Imagesmentioning

confidence: 99%

Human Monkeypox Classification from Skin Lesion Images with Deep Pre-trained Network using Mobile Application

2022

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Recently, human monkeypox outbreaks have been reported in many countries. According to the reports and studies, quick determination and isolation of infected people are essential to reduce the spread rate. This study presents an Android mobile application that uses deep learning to assist this situation. The application has been developed with Android Studio using Java programming language and Android SDK 12. Video images gathered through the mobile device’s camera are dispatched to a deep convolutional neural network that runs on the same device. Camera2 API of the Android platform has been used for camera access and operations. The network then classifies images as positive or negative for monkeypox detection. The network’s training has been carried out using skin lesion images of monkeypox-infected people and other skin lesion images. For this purpose, a publicly available dataset and a deep transfer learning approach have been used. All training and testing steps have been applied on Matlab using different pre-trained networks. Then, the network that has the best accuracy has been recreated and trained using TensorFlow. The TensorFlow model has been adapted to mobile devices by converting to the TensorFlow Lite model. The TensorFlow Lite model has been then embedded into the mobile application together with the TensorFlow Lite library for monkeypox detection. The application has been run on three devices successfully. During the run-time, the inference times have been gathered. 197 ms, 91 ms, and 138 ms average inference times have been observed. The presented system allows people with body lesions to quickly make a preliminary diagnosis. Thus, monkeypox-infected people can be encouraged to act rapidly to see an expert for a definitive diagnosis. According to the test results, the system can classify the images with 91.11% accuracy. In addition, the proposed mobile application can be trained for the preliminary diagnosis of other skin diseases.

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Cloud Computing Mobile Application for Remote Monitoring of Bell’s Palsy

Cited by 11 publications

References 14 publications

Effect of an Intensified Combined Electromyography and Visual Feedback Training on Facial Grading in Patients With Post-paralytic Facial Synkinesis

Effect of an Intensified Combined Electromyography and Visual Feedback Training on Facial Grading in Patients With Post-paralytic Facial Synkinesis

Continual rehabilitation motivation of patients with postparalytic facial nerve syndrome

Human Monkeypox Classification from Skin Lesion Images with Deep Pre-trained Network using Mobile Application

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