James M. Schafer
University of Massachusetts Amherst
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Featured researches published by James M. Schafer.
international conference of the ieee engineering in medicine and biology society | 2011
Aura Ganz; Siddhesh Rajan Gandhi; James M. Schafer; Tushar Singh; Elaine Puleo; Gary Mullett; Carole Wilson
In order to enhance the perception of indoor and unfamiliar environments for the blind and visually-impaired, we introduce the PERCEPT system that supports a number of unique features such as: a) Low deployment and maintenance cost; b) Scalability, i.e. we can deploy the system in very large buildings; c) An on-demand system that does not overwhelm the user, as it offers small amounts of information on demand; and d) Portability and ease-of-use, i.e., the custom handheld device carried by the user is compact and instructions are received audibly.
International Journal of Telemedicine and Applications | 2012
Aura Ganz; James M. Schafer; Siddhesh Rajan Gandhi; Elaine Puleo; Carole Wilson; Meg Robertson
We introduce PERCEPT system, an indoor navigation system for the blind and visually impaired. PERCEPT will improve the quality of life and health of the visually impaired community by enabling independent living. Using PERCEPT, blind users will have independent access to public health facilities such as clinics, hospitals, and wellness centers. Access to healthcare facilities is crucial for this population due to the multiple health conditions that they face such as diabetes and its complications. PERCEPT system trials with 24 blind and visually impaired users in a multistory building show PERCEPT system effectiveness in providing appropriate navigation instructions to these users. The uniqueness of our system is that it is affordable and that its design follows orientation and mobility principles. We hope that PERCEPT will become a standard deployed in all indoor public spaces, especially in healthcare and wellness facilities.
international conference of the ieee engineering in medicine and biology society | 2014
Aura Ganz; James M. Schafer; Zhuorui Yang; Jun Yi; Graydon Lord; Gregory R. Ciottone
In this paper we introduce DIORAMA-II system that provides real time information collection in mass casualty incidents. Using a mobile platform that includes active RFID tags and readers as well as Smartphones, the system can determine the location of victims and responders. The system provides user friendly multi dimensional user interfaces as well as collaboration tools between the responders and the incident commander. We conducted two simulated mass casualty incidents with 50 victims each and professional responders. DIORAMA-II significantly reduces the evacuation time by up to 43% when compared to paper based triage systems. All responders that participated in all trials were very satisfied. They felt in control of the incident and mentioned that the system significantly reduced their stress level during the incident. They all mentioned that they would use the system in an actual incident.
international conference of the ieee engineering in medicine and biology society | 2014
Aura Ganz; James M. Schafer; Yang Tao; Carole Wilson; Meg Robertson
In this paper we introduce PERCEPT-II, a low cost and user friendly indoor navigation system for blind and visually impaired users. Using an Android Smartphone that runs PERCEPT-II application with accessibility features, the blind user obtains navigation instructions to the chosen destination when touching specific landmarks tagged with Near Field Communication tags. The system was deployed and tested in a large building at the University of Massachusetts at Amherst.
international conference of the ieee engineering in medicine and biology society | 2012
Aura Ganz; James M. Schafer; Elaine Puleo; Carole Wilson; Meg Robertson
In this paper we introduce qualitative and quantitative evaluation of PERCEPT system, an indoor navigation system for the blind and visually impaired. PERCEPT system trials with 24 blind and visually impaired users in a multi-story building show PERCEPT system effectiveness in providing appropriate navigation instructions to these users. The uniqueness of our system is that it is affordable and that its design follows Orientation and Mobility principles. These results encourage us to generalize the solution to large indoor spaces and test it with significantly larger visually impaired population in diverse settings. We hope that PERCEPT will become a standard deployed in all indoor public spaces.
international conference of the ieee engineering in medicine and biology society | 2010
Aura Ganz; Xunyi Yu; James M. Schafer; Sophie D'Hauwe; Larry A. Nathanson; Jonathan L. Burstein; Gregory R. Ciottone; Graydon Lord
DIORAMA is a real-time scalable decision support framework built on rapid information collection and accurate resource tracking functionalities. Using RFID technology the proposed system tracks emergency responders and victims at the disaster scene. DIORAMA improves the accuracy and decreases the time it takes rescuers to triage, treat and evacuate victims from a disaster scene, as compared to the traditional methods and process that involves using paper triage tags. The information can then be viewed from a website that shows a satellite image of the disaster area with icons representing the paramedics and victims.
International Journal of E-health and Medical Communications | 2014
Hao Dong; Jieqi Kang; James M. Schafer; Aura Ganz
In this paper the authors introduce PERCEPT-V indoor navigation for the blind system. PERCEPT-V enhances PERCEPT system by enabling visually impaired users to navigate in open indoor spaces that differ in size and lighting conditions. The authors deploy visual tags in the environment at specific landmarks and introduce a visual tag detection algorithm using a sampling probe and cascading approach. The authors provide guidelines for the visual tag size, which is a function of various environmental, and usage scenarios, which differ in lighting, dimensions of the indoor environment and angle of usage. The authors also developed a Smartphone based user interface for the visually impaired users that uses Android accessibility features.
international conference of the ieee engineering in medicine and biology society | 2011
Hodei Iraola; James M. Schafer; Xunyi Yu; Gary Mullett; Aura Ganz
In this paper we introduce a RFID-based object management system, RiBOMS, for home environments. The system has an easy to use pictorial user interface aimed at older adults with associative memory impairments. The system technical correctness was successfully tested in a lab environment.
international conference of the ieee engineering in medicine and biology society | 2016
Aura Ganz; James M. Schafer; Zhuorui Yang; Jun Yi; Gregory R. Ciottone
In this paper we show DIORAMA efficiency in a simulated Mass Casualty Incident drill. As shown by our results DIORAMA system has achieved orderly transport of patients from site of injury to collection point, all red before the yellow were transported (no order was obeyed in the paper drills). We also show that DIORAMA system was used by responders with very short training time and by responders that are not familiar with each other. The qualitative results show that DIORAMA system was found to be user friendly and useful in tracking patients and responders in real time.
international conference of the ieee engineering in medicine and biology society | 2016
Hao Dong; Juechen Yin; James M. Schafer; Aura Ganz
In this paper we introduce DIORAMA based forensic analysis of mass casualty incidents (MCI) using video sequences. The video sequences captured on site are automatically annotated by metadata, which includes the capture time and the camera location and viewing direction. Using a visual interface the MCI investigators can easily understand the availability of video clips in specific areas of interest, and efficiently review them. The video-based forensic analysis system will enable the MCI investigators to better understand the rescue operations and subsequently improve training procedures.In this paper we introduce DIORAMA based forensic analysis of mass casualty incidents (MCI) using video sequences. The video sequences captured on site are automatically annotated by metadata, which includes the capture time and the camera location and viewing direction. Using a visual interface the MCI investigators can easily understand the availability of video clips in specific areas of interest, and efficiently review them. The video-based forensic analysis system will enable the MCI investigators to better understand the rescue operations and subsequently improve training procedures.