Utilizing an Augmented Reality System to Address Phantom Limb Syndrome in a Cloud-Based Environment

Author(s):  
Afeef Sheikh

Phantom Limb Syndrome (PLS) is the perception of sensations, often including chronic intense pain localized to the site of an amputated or denervated limb. This syndrome is relatively common in amputees; the pain often reflects the amount of pre-amputation pain, and is often refractory to excision of amputation neuroma, rubbing, electrical stimulation, peripheral nerve or spinal blocks, narcotics, and sympathectomy (Alviar et al., 2011). Mirror therapy, a present method of rehabilitation, is estimated to be only 60% effective in upper limb amputees while also requiring expensive equipment and monitoring by a caretaker or technician. This paper is aimed at designing an affordable, effective, and accessible alternative solution to address the rehabilitation challenges associated with PLS. Using the power of Augmented Reality (AR) coupled with open source software, such as Unity3D and Vuforia, and commonly used devices like cellphones and computers, the prototype can read muscle activity and create an onscreen image of a virtual hand in place-of the individual's lost hand and can mimic basic hand movements through the use of an AR camera. Due to the limited processing power present within most cellphones, the solution is being refined to capitalize on Cloud computing. In doing so, the hand model can be rendered offsite and streamed directly to the phone, resulting in a higher equality image. The efficacy of this solution has not yet been tested on human subjects by virtue of legal restrictions. This system is currently being forwarded to qualified individuals who have the necessary credentials to perform clinical trials in a certified lab environment.

2018 ◽  
Vol 32 (12) ◽  
pp. 1591-1608 ◽  
Author(s):  
Andreas Rothgangel ◽  
Susy Braun ◽  
Bjorn Winkens ◽  
Anna Beurskens ◽  
Rob Smeets

Objective: To compare the effects of traditional mirror therapy (MT), a patient-centred teletreatment (PACT) and sensomotor exercises without a mirror on phantom limb pain (PLP). Design: Three-arm multicentre randomized controlled trial. Setting: Rehabilitation centres, hospital and private practices. Subjects: Adult patients with unilateral lower limb amputation and average PLP intensity of at least 3 on the 0–10 Numeric Rating Scale (NRS). Interventions: Subjects randomly received either four weeks of traditional MT followed by a teletreatment using augmented reality MT, traditional MT followed by self-delivered MT or sensomotor exercises of the intact limb without a mirror followed by self-delivered exercises. Main measures: Intensity, frequency and duration of PLP and patient-reported outcomes assessing limitations in daily life at baseline, 4 weeks, 10 weeks and 6 months. Results: In total, 75 patients received traditional MT ( n = 25), teletreatment ( n = 26) or sensomotor exercises ( n = 24). Mean (SD) age was 61.1 (14.2) years and mean (SD) pain intensity was 5.7 (2.1) on the NRS. Effects of MT at four weeks on PLP were not significant. MT significantly reduced the duration of PLP at six months compared to the teletreatment ( P = 0.050) and control group ( P = 0.019). Subgroup analyses suggested significant effects on PLP in women, patients with telescoping and patients with a motor component in PLP. The teletreatment had no additional effects compared to self-delivered MT at 10 weeks and 6 months. Conclusion: Traditional MT over four weeks was not more effective than sensomotor exercises without a mirror in reducing PLP, although significant effects were suggested in some subgroups.


Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3061
Author(s):  
Alice Lo Valvo ◽  
Daniele Croce ◽  
Domenico Garlisi ◽  
Fabrizio Giuliano ◽  
Laura Giarré ◽  
...  

In recent years, we have assisted with an impressive advance in augmented reality systems and computer vision algorithms, based on image processing and artificial intelligence. Thanks to these technologies, mainstream smartphones are able to estimate their own motion in 3D space with high accuracy. In this paper, we exploit such technologies to support the autonomous mobility of people with visual disabilities, identifying pre-defined virtual paths and providing context information, reducing the distance between the digital and real worlds. In particular, we present ARIANNA+, an extension of ARIANNA, a system explicitly designed for visually impaired people for indoor and outdoor localization and navigation. While ARIANNA is based on the assumption that landmarks, such as QR codes, and physical paths (composed of colored tapes, painted lines, or tactile pavings) are deployed in the environment and recognized by the camera of a common smartphone, ARIANNA+ eliminates the need for any physical support thanks to the ARKit library, which we exploit to build a completely virtual path. Moreover, ARIANNA+ adds the possibility for the users to have enhanced interactions with the surrounding environment, through convolutional neural networks (CNNs) trained to recognize objects or buildings and enabling the possibility of accessing contents associated with them. By using a common smartphone as a mediation instrument with the environment, ARIANNA+ leverages augmented reality and machine learning for enhancing physical accessibility. The proposed system allows visually impaired people to easily navigate in indoor and outdoor scenarios simply by loading a previously recorded virtual path and providing automatic guidance along the route, through haptic, speech, and sound feedback.


2013 ◽  
Vol 60 (9) ◽  
pp. 2636-2644 ◽  
Author(s):  
Hussam Al-Deen Ashab ◽  
Victoria A. Lessoway ◽  
Siavash Khallaghi ◽  
Alexis Cheng ◽  
Robert Rohling ◽  
...  

2009 ◽  
Vol 5 (4) ◽  
pp. 415-422 ◽  
Author(s):  
Ramesh Thoranaghatte ◽  
Jaime Garcia ◽  
Marco Caversaccio ◽  
Daniel Widmer ◽  
Miguel A. Gonzalez Ballester ◽  
...  

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