No abstract

Online social media is widespread, easily accessible and attracts a global audience with a widening demographic. As a large proportion of adults now seek health information online and through social media applications, communication about health has become increasingly interactive and dynamic. Online health information has the potential to significantly impact public health, especially as the population gets older and the prevalence of dementia increases. However, little is known about how information pertaining to age-associated diseases is disseminated on popular social media platforms. To fill this knowledge gap, we examined empirically: (i) who is using social media to share information about dementia, (ii) what sources of information about dementia are promoted, and (iii) which dementia themes dominate the discussion. We data-mined the microblogging platform Twitter for content containing dementia-related keywords for a period of 24 hours and retrieved over 9,200 tweets. A coding guide was developed and content analysis conducted on a random sample (10%), and on a subsample from top users’ tweets to assess impact. We found that a majority of tweets contained a link to a third party site rather than personal information, and these links redirected mainly to news sites and health information sites. As well, a large number of tweets discussed recent research findings related to the prediction and risk management of Alzheimer’s disease. The results highlight the need for the dementia research community to harness the reach of this medium and its potential as a tool for multidirectional engagement.

Binocular eye-gaze tracking can be used to estimate the point-of-gaze (POG) of a subject in real-world 3-D space using the vergence of the eyes. In this paper, a novel noncontact model-based technique for 3-D POG estimation is presented. The noncontact system allows people to select real-world objects in 3-D physical space using their eyes, without the need for head-mounted equipment. Remote 3-D POG estimation may be especially useful for persons with quadriplegia or Amyotrophic Lateral Sclerosis. It would also enable a user to select 3-D points in space generated by 3-D volumetric displays, with potential applications to medical imaging and telesurgery. Using a model-based POG estimation algorithm allows for free head motion and a single stage of calibration. It is shown that an average accuracy of 3.93 cm was achieved over a workspace volume of 30 x 23 x 25 cm (W x H x D) with a maximum latency of 1.5 s due to the digital filtering employed. The users were free to naturally move and reorient their heads while operating the system, within an allowable headspace of 3 cm x 9 cm x 14 cm.

No abstract

Social media is broadening opportunities to engage in discussions about biomedical advances such as stem cell research. However, little is known about how information pertaining to stem cells is disseminated on platforms such as Twitter. To fill this gap, we conducted a content analysis of tweets containing (i) a stem cell keyword, and (ii) a keyword related to either spinal cord injury (SCI) or Parkinson disease (PD). We found that the discussion about stem cells and SCI or PD revolves around different aspects of the research process. We also found that the tone of most tweets about stem cells is either positive or neutral. The findings contribute new knowledge about Twitter as a connecting platform for many voices and as a key tool for the dissemination of information about stem cells and disorders of the central nervous system.