Wearable cameras in health: the state of the art and future possibilities.

The relationships between lifestyle behaviors and health outcomes usually are based on self-reported data. Such data are prone to measurement error. In response, there has been a movement towards objective forms of measurement that have low participant and researcher burden. The papers in this theme issue in the American Journal of Preventive Medicine assess the utility of a new form of objective measurement in health research, namely wearable cameras. These devices can be worn all day and automatically record images from a first-person point of view, requiring no intervention or attention from the subject or the researcher. The most mature visual lifelogging device is Microsoft's SenseCam, a wearable camera worn via a lanyard around the neck. The SenseCam has been increasingly used in health-related research for several years. These theme papers report current research into wearable cameras in health, as presented at the SenseCam 2012 Symposium. Wearable cameras and their associated software analysis tools have developed to the point that they now appear well suited to measure sedentary behaviour, active travel, and nutrition-related behaviours. Individuals may recall events more accurately after reviewing images from their wearable cameras. Aspects of their immediate cognitive functioning may also improve. Despite the benefits of wearable cameras, there are still challenges remaining before their use becomes widespread. Ethical and privacy concerns are important issues that need to be addressed, as well as easy access to devices. In response, an ethical framework and smartphone-based wearable camera capture platform are proposed. In sum, this body of work suggests that the use of wearable cameras will soon be appropriate to understand lifestyle behaviours and the context in which the occur.

[1]  Cathal Gurrin,et al.  The smartphone as a platform for wearable cameras in health research. , 2013, American journal of preventive medicine.

[2]  Andrew Bateman,et al.  Exploration of use of SenseCam to support autobiographical memory retrieval within a cognitive-behavioural therapeutic intervention following acquired brain injury , 2011, Memory.

[3]  J. Burke,et al.  Feasibility Testing of an Automated Image-Capture Method to Aid Dietary Recall , 2011, European Journal of Clinical Nutrition.

[4]  G. O'loughlin,et al.  Using a wearable camera to increase the accuracy of dietary analysis. , 2013, American journal of preventive medicine.

[5]  C. Moulin,et al.  Benefits of SenseCam review on neuropsychological test performance. , 2013, American journal of preventive medicine.

[6]  Jim Gemmell,et al.  Total Recall: How the E-Memory Revolution Will Change , 2009 .

[7]  David S. Ebert,et al.  The Use of Mobile Devices in Aiding Dietary Assessment and Evaluation , 2010, IEEE Journal of Selected Topics in Signal Processing.

[8]  Shahram Izadi,et al.  SenseCam: A Retrospective Memory Aid , 2006, UbiComp.

[9]  L. Mâsse,et al.  Physical activity in the United States measured by accelerometer. , 2008, Medicine and science in sports and exercise.

[10]  Neil Armstrong,et al.  The Physical Activity Patterns of European Youth with Reference to Methods of Assessment , 2006, Sports medicine.

[11]  Steve Hodges,et al.  Can we use digital life-log images to investigate active and sedentary travel behaviour? Results from a pilot study , 2011, The international journal of behavioral nutrition and physical activity.

[12]  Hannah Badland,et al.  Use of wearable cameras to assess population physical activity behaviours: an observational study , 2012, The Lancet.

[13]  Katalin Pauly-Takacs,et al.  SenseCam as a rehabilitation tool in a child with anterograde amnesia , 2011, Memory.

[14]  Vannevar Bush,et al.  As we may think , 1945, INTR.

[15]  Steve Mann,et al.  Wearable Computing: A First Step Toward Personal Imaging , 1997, Computer.

[16]  S. Marshall,et al.  Using the SenseCam to improve classifications of sedentary behavior in free-living settings. , 2013, American journal of preventive medicine.

[17]  Mingui Sun,et al.  Imaged based estimation of food volume using circular referents in dietary assessment. , 2012, Journal of food engineering.

[18]  Alan F. Smeaton,et al.  Experiences of Aiding Autobiographical Memory Using the SenseCam , 2012, Hum. Comput. Interact..

[19]  Wendy Hall,et al.  A low-power, distributed, pervasive healthcare system for supporting memory , 2011, MobileHealth '11.

[20]  P. Kelly,et al.  Evaluating the Feasibility of Measuring Travel to School Using a Wearable Camera , 2012, American journal of preventive medicine.

[21]  D. J. van der Valk,et al.  How accurately can sitting and the intensity of walking and cycling be classified using an accelerometer on the waist for the purpose of the “Global recommendations on physical activity for health”? , 2015 .

[22]  Kiyoharu Aizawa,et al.  Summarizing wearable video , 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).

[23]  S. Marshall,et al.  An ethical framework for automated, wearable cameras in health behavior research. , 2013, American journal of preventive medicine.

[24]  J F Sallis,et al.  Behavioral epidemiology: A systematic framework to classify phases of research on health promotion and disease prevention , 2000, Annals of behavioral medicine : a publication of the Society of Behavioral Medicine.

[25]  Alan F. Smeaton,et al.  Passively recognising human activities through lifelogging , 2011, Comput. Hum. Behav..

[26]  G. Rose Sick individuals and sick populations. , 2001, International journal of epidemiology.

[27]  A. Owen,et al.  The neural basis of effective memory therapy in a patient with limbic encephalitis , 2009, Journal of Neurology Neurosurgery & Psychiatry.