Fall Classification by Machine Learning Using Mobile Phones

Fall prevention is a critical component of health care; falls are a common source of injury in the elderly and are associated with significant levels of mortality and morbidity. Automatically detecting falls can allow rapid response to potential emergencies; in addition, knowing the cause or manner of a fall can be beneficial for prevention studies or a more tailored emergency response. The purpose of this study is to demonstrate techniques to not only reliably detect a fall but also to automatically classify the type. We asked 15 subjects to simulate four different types of falls–left and right lateral, forward trips, and backward slips–while wearing mobile phones and previously validated, dedicated accelerometers. Nine subjects also wore the devices for ten days, to provide data for comparison with the simulated falls. We applied five machine learning classifiers to a large time-series feature set to detect falls. Support vector machines and regularized logistic regression were able to identify a fall with 98% accuracy and classify the type of fall with 99% accuracy. This work demonstrates how current machine learning approaches can simplify data collection for prevention in fall-related research as well as improve rapid response to potential injuries due to falls

Modelling mammalian energetics: the heterothermy problem

Global climate change is expected to have strong effects on the world’s flora and fauna. As a result, there has been a recent increase in the number of meta-analyses and mechanistic models that attempt to predict potential responses of mammals to changing climates. Many models that seek to explain the effects of environmental temperatures on mammalian energetics and survival assume a constant body temperature. However, despite generally being regarded as strict homeotherms, mammals demonstrate a large degree of daily variability in body temperature, as well as the ability to reduce metabolic costs either by entering torpor, or by increasing body temperatures at high ambient temperatures. Often, changes in body temperature variability are unpredictable, and happen in response to immediate changes in resource abundance or temperature. In this review we provide an overview of variability and unpredictability found in body temperatures of extant mammals, identify potential blind spots in the current literature, and discuss options for incorporating variability into predictive mechanistic models

Erratum to: Scaling up strategies of the chronic respiratory disease programme of the European Innovation Partnership on Active and Healthy Ageing (Action Plan B3: Area 5).

[This corrects the article DOI: 10.1186/s13601-016-0116-9.]

Erratum to: Scaling up strategies of the chronic respiratory disease programme of the European Innovation Partnership on Active and Healthy Ageing (Action Plan B3: Area 5).

[This corrects the article DOI: 10.1186/s13601-016-0116-9.]

Improved patient satisfaction using ingenol mebutate gel 0.015% for the treatment of facial actinic keratoses: a prospective pilot study

Joanna Emilio,1 Michelle Schwartz,2–4 Eleanor Feldman,2–4 Amy Kalowitz Bieber,2–4 Amanda Bienenfeld,2–4 Min-Kyung Jung,1 Daniel M Siegel,2,3 Orit Markowitz2–4 1Department of Dermatology, NYIT College of Osteopathic Medicine, Old Westbury, 2Department of Dermatology, SUNY Downstate Medical Center, 3Department of Dermatology, NY Harbor Healthcare System, Brooklyn, 4Department of Dermatology, Mount Sinai Medical Center, New York, NY, USA Abstract: Actinic keratoses (AKs), especially on areas of the face, have a negative impact on a patient's quality of life (QoL). These lesions manifest on sun-damaged skin and have the potential to progress to squamous cell carcinoma. Field-directed therapy alone and in combination with lesion-directed treatment is effective in clearing both visible and nonvisible AK lesions. Topical treatments of AKs thus have the potential to improve a patient's well-being. However, evidence demonstrating improvements in patient QoL is limited, and is mostly based on observational or retrospective studies. Some prospective studies have reported unchanged or even worsening QoL despite excellent treatment outcomes. Our prospective, pilot study demonstrated a significant increase in QoL in 28 subjects with AKs of the face treated with ingenol mebutate gel 0.015%. QoL was assessed at days 0 and 60 using the Skindex-16 survey. Mean overall scores improved from 24.5% at baseline to 15.5% at day 60 (P=0.031). Improvements in QoL were consistent with an 80% reduction in AK lesion number at day 60. These improved QoL findings are in line with those from a recent retrospective study using ingenol mebutate 0.015% gel. This study therefore further demonstrates the potential for field therapy to improve both treatment outcomes and patient satisfaction. Keywords: actinic keratosis, squamous cell carcinoma, ingenol mebutate gel, local skin reaction, quality of life, Skindex-1