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To evaluate acceptability of 3-dimensional virtual reality (3dVR) technology for upper extremity weakness after stroke. Prospective, single center, pilot study. Freestanding rehabilitation hospital. Participants referred by occupational therapists. Inclusion criteria:18 years or older; ischemic or hemorrhagic stroke within 3 months; Fugl-Meyer of ≥14; follow commands; maintain upright sitting; and BIMS score of ≥7. Exclusion criteria included non-stroke related upper extremity weakness; history of seizures/epilepsy; history of orthopedic shoulder injury; Modified Ashworth scale >2 upper extremities; active cyber sickness symptoms; vestibular issues; contact isolation; legal blindness; and pregnancy. Clinical staff trained with 3dVR system implemented task specific protocol as part of standard care. Enrolled subjects received 6 thirty minutes 3dVR sessions adjunctive to standard therapy. 3dVR sessions were customized with modifications to ensure appropriate challenge. Post treatment, participants responded to questions regarding safety. After six sessions, participants reassessed with clinical outcome measures. Acceptability assessed with 7-point Likert questionnaire; safety with Simulator Sickness Symptomology questionnaire; clinical outcomes using Care Tool, UE Fugl-Meyer, and Patient Specific Functional Scale (PSFS). : Eleven participants enrolled with six completing the protocol. Five subjects were discharged prior to completion of protocol, their partial data has been synthesized. Age range 53-82 years [Mean=65.6; SD±11.27], with sex distribution 36.36% male/ 63.64% female. Average onset time of stroke to enrollment 7.82 days. Participants who completed the protocol, average Fugl-Meyer change score was 11.67; PSFS increased by 3.81; Care Tool change 15.99. Single participant experienced dizziness with intervention, however overall patients tolerated 3dVR. The pilot data revealed relatively good tolerance for 3dVR therapy with majority experiencing no adverse effects. Preliminary data shows promise; however, further research is needed with a larger sample size to confirm pilot data. The authors of this pilot study have no disclosures to declare. [ABSTRACT FROM AUTHOR]

In this paper, we study the benefits of the availability of a specific form of additional information—the vertical direction (gravity) and the height of the camera, both of which can be conveniently measured using inertial sensors and a monocular video sequence for 3D urban modeling. We show that in the presence of this information, the SfM equations can be rewritten in a bilinear form. This allows us to derive a fast, robust, and scalable SfM algorithm for large scale applications. The SfM algorithm developed in this paper is experimentally demonstrated to have favorable properties compared to the sparse bundle adjustment algorithm. We provide experimental evidence indicating that the proposed algorithm converges in many cases to solutions with lower error than state-of-art implementations of bundle adjustment. We also demonstrate that for the case of large reconstruction problems, the proposed algorithm takes lesser time to reach its solution compared to bundle adjustment. We also present SfM results using our algorithm on the Google StreetView research data set. [ABSTRACT FROM AUTHOR]