Evaluation of an open source method for calculating physical activity in dogs from harness and collar based sensors

Abstract Background The ability to make objective measurements of physical activity in dogs has both clinical and research applications. Accelerometers offer a non-intrusive and convenient solution. Of the commercialy available sensors, measurements are commonly given in manufacturer bespoke units and calculated with closed source approaches. Furthermore, the validation studies that exist for such devices are mounting location dependant, not transferable between brands or not suitable for handling modern raw accelerometry type data. Methods This paper describes a validation study of n = 5 where 4 sensors were placed on each dog; 2 on a harness and 2 on a collar. Each position held two sensors from different manufacturers; Actigraph (which has previously been validated for use on the collar) and VetSens (which provides un-filtered accelerometry data). The aims of the study was to firstly evaluate the performance of an open-design method of converting raw accelerometry data into units that have previously been validated. Secondly, comparison was made between sensors mounted at each location for determining physical activity state. Results Once the raw actigraphy data had been processed with the open-design method, results from a 7 day measurement revealed no significant difference in physical activity estimates via a cutpoint approach between the sensor manufacturers. A second finding was a low inter-site variability between the ventral collar and dorsal harness locations (Pearsons r2 = 0.96). Conclusions Using the open-design methodology, raw, un-filtered data from the VetSens sensors can be compared or pooled with data gathered from Actigraph sensors. The results also provide strong evidence that ventral collar and dorsal harness sites may be used interchangeably. This enables studies to be designed with a larger inclusion criteria (encompassing dogs that are not well suited for wearing an instrumented collar) and ensures high levels of welfare while maintaining measurement validity

A study of wrist-worn activity measurement as a potential real-world biomarker for late-life depression.

BACKGROUND: Late-life depression (LLD) is associated with a decline in physical activity. Typically this is assessed by self-report questionnaires and, more recently, with actigraphy. We sought to explore the utility of a bespoke activity monitor to characterize activity profiles in LLD more precisely. METHOD: The activity monitor was worn for 7 days by 29 adults with LLD and 30 healthy controls. Subjects underwent neuropsychological assessment and quality of life (QoL) (36-item Short-Form Health Survey) and activities of daily living (ADL) scales (Instrumental Activities of Daily Living Scale) were administered. RESULTS: Physical activity was significantly reduced in LLD compared with controls (t = 3.63, p < 0.001), primarily in the morning. LLD subjects showed slower fine motor movements (t = 3.49, p < 0.001). In LLD patients, activity reductions were related to reduced ADL (r = 0.61, p < 0.001), lower QoL (r = 0.65, p < 0.001), associative learning (r = 0.40, p = 0.036), and higher Montgomery-Åsberg Depression Rating Scale score (r = -0.37, p < 0.05). CONCLUSIONS: Patients with LLD had a significant reduction in general physical activity compared with healthy controls. Assessment of specific activity parameters further revealed the correlates of impairments associated with LLD. Our study suggests that novel wearable technology has the potential to provide an objective way of monitoring real-world function.This study was funded by an award from the UK Medical Research Council (G1001828/1)

A step in the right direction: an open-design pedometer algorithm for dogs

Accelerometer-based technologies could be useful in providing objective measures of canine ambulation, but most are either not tailored to the idiosyncrasies of canine gait, or, use un-validated or closed source approaches. The aim of this paper was to validate algorithms which could be applied to accelerometer data for i) counting the number of steps and ii) distance travelled by a dog.To count steps, an approach based on partitioning acceleration was used. This was applied to accelerometer data from 13 dogs which were walked a set distance and filmed. Each footfall captured on video was annotated. In a second experiment, an approach based on signal features was used to estimate distance travelled. This was applied to accelerometer data from 10 dogs with osteoarthritis during normal walks with their owners where GPS (Global Positioning System) was also captured. Pearson’s correlations and Bland Altman statistics were used to compare i) the number of steps measured on video footage and predicted by the algorithm and ii) the distance travelled estimated by GPS and predicted by the algorithm

Global nitrogen budgets in cereals: A 50-year assessment for maize, rice, and wheat production systems

Industrially produced N-fertilizer is essential to the production of cereals that supports current and projected human populations. We constructed a top-down global N budget for maize, rice, and wheat for a 50-year period (1961 to 2010). Cereals harvested a total of 1551 Tg of N, of which 48% was supplied through fertilizer-N and 4% came from net soil depletion. An estimated 48% (737 Tg) of crop N, equal to 29, 38, and 25 kg ha−1 yr−1 for maize, rice, and wheat, respectively, is contributed by sources other than fertilizer- or soil-N. Non-symbiotic N2 fixation appears to be the major source of this N, which is 370 Tg or 24% of total N in the crop, corresponding to 13, 22, and 13 kg ha−1 yr−1 for maize, rice, and wheat, respectively. Manure (217 Tg or 14%) and atmospheric deposition (96 Tg or 6%) are the other sources of N. Crop residues and seed contribute marginally. Our scaling-down approach to estimate the contribution of non-symbiotic N2 fixation is robust because it focuses on global quantities of N in sources and sinks that are easier to estimate, in contrast to estimating N losses per se, because losses are highly soil-, climate-, and crop-specific

The 4 per 1000 initiative.

Soil organic matter is at the nexus of global challenges: food security, climate change adaptation and mitigation, soil security. The 4 per 1000 initiative, launched at the Climate COP21 within the Lima-Paris Action Agenda proposes to increase soil organic carbon (SOC) stocks to simultaneously address all these challenges. It directly addresses three sustainable development goals: SDG2 ?no hunger?, SDG13 ?Climate action?, and SDG15 ?Life on land? and indirectly concerns several others. The initiative targets agricultural soils in priority, which are often the most degraded soils and because of the high expected benefits in terms of soil fertility and hence of productivity. A range of agricultural practices are available that allow to increase SOC stocks while ensuring a resilient, productive and environmentally friendly agriculture, so that a large-scale deployment can be aimed at. Here, we review and discuss the main limits and criticisms addressed to the 4 per 1000 initiative

Instrumented gait assessment with a single wearable: an introductory tutorial

Gait is a powerful tool to identify ageing and track disease progression. Yet, its measurement via traditional instrumentations remains restricted to the laboratory or bespoke clinical facilities. The potential for that to change is due to the advances in wearable technology where the synergy between accelerometer-based body worn monitors and smart algorithms has provided the potential of ‘a gait lab on a chip’. The deployment of wearables can allow the researcher/clinician to continuously assess the participant accurately and robustly over time. Commercially available wearables for gait quantification remain expensive and are restricted to a limited number of characteristics unsuitable for a comprehensive clinical assessment. However, the increasing demand for low cost diagnostics has fuelled the shift in how health-related resources are distributed. As such the interest in open platform technology and novel research methodologies has begun to harmonise engineering solutions with clinical needs. We provide an introduction to conduct an instrumented gait assessment with a discrete, low cost, accelerometer-based body worn monitor. We show that the capture and interpretation of raw gait signals with a common scripting language (MATLAB®) can be straightforward. In addition, we highlight best approaches and hope that this will help compliment any analytical tool-kit as part of any modern clinical assessment

Auditable, Available and Resilient Private Computation on the Blockchain via MPC

Simple but mission-critical internet-based applications that require extremely high reliability, availability, and verifiability (e.g., auditability) could benefit from running on robust public programmable blockchain platforms such as Ethereum. Unfortunately, program code running on such blockchains is normally publicly viewable, rendering these platforms unsuitable for applications requiring strict privacy of application code, data, and results. In this work, we investigate using MPC techniques to protect the privacy of a blockchain computation. While our main goal is to hide both the data and the computed function itself, we also consider the standard MPC setting where the function is public. We describe GABLE (Garbled Autonomous Bots Leveraging Ethereum), a blockchain MPC architecture and system. The GABLE architecture specifies the roles and capabilities of the players. GABLE includes two approaches for implementing MPC over blockchain: Garbled Circuits (GC), evaluating universal circuits, and Garbled Finite State Automata (GFSA). We formally model and prove the security of GABLE implemented over garbling schemes, a popular abstraction of GC and GFSA from (Bellare et al, CCS 2012). We analyze in detail the performance (including Ethereum gas costs) of both approaches and discuss the trade-offs. We implement a simple prototype of GABLE and report on the implementation issues and experience

Coupling Optical and Electrical Measurements in Artificial Membranes: Lateral Diffusion of Lipids and Channel Forming Peptides in Planar Bilayers

Planar lipid bilayers (PLB) were prepared by the Montal-Mueller technique in a FRAP system designed to simultaneously measure conductivity across, and lateral diffusion of, the bilayer. In the first stage of the project the FRAP system was used to characterise the lateral dynamics of bilayer lipids with regards to phospholipid composition (headgroup, chain unsaturation etc.), presence of cholesterol and the effect of divalent cations on negatively-charged bilayers. In the second stage of the project, lateral diffusion of two fluorescently-labelled voltage-dependent pore-forming peptides (alamethicin and S4s from Shaker K(+) channel) was determined at rest and in the conducting state. This study demonstrates the feasibility of such experiments with PLBs, amenable to physical constraints, and thus offers new opportunities for systematic studies of structure-function relationships in membrane-associating molecules

Longitudinal biomarkers in amyotrophic lateral sclerosis

OBJECTIVE: To investigate neurodegenerative and inflammatory biomarkers in people with amyotrophic lateral sclerosis (PALS), evaluate their predictive value for ALS progression rates, and assess their utility as pharmacodynamic biomarkers for monitoring treatment effects. METHODS: De-identified, longitudinal plasma, and cerebrospinal fluid (CSF) samples from PALS (n = 108; 85 with samples from \u3e /=2 visits) and controls without neurological disease (n = 41) were obtained from the Northeast ALS Consortium (NEALS) Biofluid Repository. Seventeen of 108 PALS had familial ALS, of whom 10 had C9orf72 mutations. Additional healthy control CSF samples (n = 35) were obtained from multiple sources. We stratified PALS into fast- and slow-progression subgroups using the ALS Functional Rating Scale-Revised change rate. We compared cytokines/chemokines and neurofilament (NF) levels between PALS and controls, among progression subgroups, and in those with C9orf72 mutations. RESULTS: We found significant elevations of cytokines, including MCP-1, IL-18, and neurofilaments (NFs), indicators of neurodegeneration, in PALS versus controls. Among PALS, these cytokines and NFs were significantly higher in fast-progression and C9orf72 mutation subgroups versus slow progressors. Analyte levels were generally stable over time, a key feature for monitoring treatment effects. We demonstrated that CSF/plasma neurofilament light chain (NFL) levels may predict disease progression, and stratification by NFL levels can enrich for more homogeneous patient groups. INTERPRETATION: Longitudinal stability of cytokines and NFs in PALS support their use for monitoring responses to immunomodulatory and neuroprotective treatments. NFs also have prognostic value for fast-progression patients and may be used to select similar patient subsets in clinical trials