Cost benefit analysis of automatic lameness detection systems in dairy herds: A dynamic programming approach.

Epidemiological data establish that lameness is second only to mastitis as the dairy industry's most prevalent and costly animal welfare issue. Using an automatic lameness detection (ALD) system in which continuous, accurate detection is coupled with proper treatment, is key for reducing economic losses due to lameness. It is reasonable to assume that the cost of lameness would vary with its severity. Therefore, our first objective was to estimate the cost of different lameness severity levels as a function of milk production, lameness risk, conception probability, and treatment cost using a dynamic programming (DP) model. Our second objective was to conduct a cost benefit analysis for ALD systems which can reduce production losses through early detection and treatment of lameness, when compared to visual-detection (VD; i.e., performed by humans) systems. The default production loss parameters for the VD system used as inputs to the DP model were either sourced from the literature or were estimated based on data from a field trial. The production loss parameters for the ALD system used as inputs to the DP model were based on extrapolations of parameter values used for the VD system. The profit per present cow per year under assumed expenses and revenues decreased from $426.05 (when lameness incidence was assumed to be 0%) to $389.69 when lameness incidence was 19.5 %. Out of the 19.5 % lameness incidence in our default scenario, 9.8 % were moderate cases and 9.7 % were severe cases. Average cost of lameness was $36.36 at 19.5 % incidence. Average cost of lameness increased with increased incidence and was respectively $82.05, $195.05, and $286.87 at the low, medium, and high incidence scenarios. We used an operational framework which compared the lameness costs between the VD and ALD systems with 25 %, 50 % and 75 % net avoided costs (NAC) for the 10 year lifespan of the ALD system, at default, low, medium and high lameness incidence scenarios. The net return per cow per year from using an ALD system over a VD system was $13, at low incidence and 25 % NAC. The net return per cow per year for the ALD system was as high as $99 at high incidence and 75 % NAC. Out of 351 (3 system prices, 3 system efficiencies, 3 levels of lameness incidence and 13 different herd sizes) scenarios tested, 295 resulted in a net profit within the system lifespan of 10 years, thus justifying the investment in ALD systems.

Enhancing the prediction accuracy of bovine lameness models through transformations of limb movement variables.

The issue of modeling bovine lameness was explored by testing the hypothesis that B-spline transformation of limb movement variables (LMV) employed in predictive models improved model accuracy. The objectives were to determine the effect of number of B-spline knots and the degree of the underlying polynomial approximation (degree of freedom) on model accuracy. Knot number used in B-spline transformation improved model accuracy by improving model specificity and to a lesser extent model sensitivity. Degree of polynomial approximation had no effect on model predictive accuracy from the data set of 261 cows. Model stability, defined as changes in predictive accuracy associated with the superimposition of perturbations (0.5 and 1.0%) in LMV on the measured data, was explored. Model specificity and to a lesser degree, sensitivity, increased with increased knot number across data set perturbations. Specificity and sensitivity increased by 43 and 11%, respectively, when knot number increased from 0 to 7 for a perturbation level of 0.5%. When the perturbation level was 1%, the corresponding increases in specificity and sensitivity were 32 and 4%, respectively. Nevertheless, different levels of LMV perturbation varied the optimal knot number associated with highest model accuracy. The optimal knot number for 0.5% perturbation was 8, whereas for 1% perturbation the optimal knot number was 7. The B-spline transformation improved specificity and sensitivity of predictive models for lameness, provided the appropriate number of knots was selected.

Objective determination of claw pain and its relationship to limb locomotion score in dairy cattle.

We hypothesized that claw and foot pain could be objectively determined and have a strong effect on limb locomotion. Claw pain was measured using hoof testers equipped with a pressure gauge. Soft tissue pain was evaluated with an algometer. Pain was determined as the maximum pressure recorded at the time the limb was withdrawn following claw or soft tissue compression with the hoof tester or algometer. Locomotion scores and claw and soft tissue pain were determined on 263 Holstein cows from 2 commercial dairy farms. The frequency and the magnitude of pain had an effect on locomotion score in the ipsilateral limb for lateral, but not medial, claws. The magnitude of the lateral claw pain index for limbs with locomotion scores 1 to 5 was 0.95 +/- 0.01, 0.90 +/- 0.02, 0.67 +/- 0.04, 0.65 +/- 0.05, and 0.45 +/- 0.11, respectively. The magnitude of the medial claw pain index for limbs with locomotion scores 1 to 5 was 1.0 +/- 0.00, 0.99 +/- 0.01, 0.98 +/- 0.01, 1.0 +/- 0.00, and 1.0 +/- 0.00, respectively. The frequency of painful claws (n = 208) in limbs with locomotion scores 1, 2, and > or =3 was 0.529, 0.173, and 0.298, respectively. The frequency of painless claws (n = 318) in limbs with locomotion scores 1, 2, or > or =3 was 0.792, 0.088, and 0.120, respectively. The frequency of pain (27.1%) and total lesions (85.6%) was greater in lateral claws (n = 524) than that of pain (2.1%) and total lesions (14.4%) in medial claws (n = 524). Yet the magnitude of the pain index in sore claws was similar for medial (0.73 +/- 0.09) and lateral claws (0.64 +/- 0.02). The magnitude and frequency of claw pain in one hind limb was inconsistently and weakly affected by locomotion score or claw pain in the contralateral limb. The prevalence of unilateral (32.8%) and bilateral (23.3%) pain was similar and lower than the occurrence of bilaterally nonpainful claws (43.9%) in the study group. Painful claws (n = 78) occurred on sound limbs (n = 332) with a pain index (0.72 +/- 0.02) indicative of less pain than the pain index (0.61 +/- 0.02) of painful claws (n = 130) on lame limbs (n = 192). The results showed that lateral claw pain was related to ipsilateral limb locomotion score and subclinical pain was a relatively common occurrence. Objective measures of pain may provide a more reliable, continuous measure of clinical events used in modeling lameness.

Comparison of models to identify lame cows based on gait and lesion scores, and limb movement variables.

Bovine lameness results in pain and suffering in cattle and economic loss for producers. A system for automatically detecting lame cows was developed recently that measures vertical force components attributable to individual limbs. These measurements can be used to calculate a number of limb movement variables. The objective of this investigation was to explore whether gait scores, lesion scores, or combined gait and lesion scores were more effectively captured by a set of 5 limb movement variables. A set of 700 hind limb examinations was used to create gait-based, lesion-based, and combined (gait- and lesion-based) models. Logistic regression models were constructed using 1, 2, or 3 d of measurements. Resulting models were tested on cows not used in modeling. The accuracy of lesion-score models was superior to that of gait-score models; lesion-based models generated greater values of areas under the receiving operating characteristic curves (range 0.75 to 0.84) and lower mean-squared errors (0.13 to 0.16) compared with corresponding values for the gait-based models (0.63 to 0.73 and 0.26 to 0.31 for receiving operating characteristic and mean-squared errors, respectively). These results indicate that further model development and investigation could generate automated and objective methods of lameness detection in dairy cattle.

A noninvasive radiotelemetry system to monitor heart rate for assessing stress responses of bovines.

A noninvasive radiotelemetry system was developed to monitor heart rates of cows and to view and analyze data. The system was validated by comparing heart rate data of two restrained heifers collected simultaneously using telemetric and direct electrocardiogram measurements and by acquiring data over 72 h from two dry cows housed in an experimental handling facility consisting of a free-stall pen, a holding pen, a pass-through stall, and a second holding pen. Telemetric and direct measurements in response to pharmacological elevation of heart rates were essentially identical. For cows in the experimental facility, peristimulus-time histograms indexed to standing or lying showed that average heart rates for cows increased 4.0 +/- 1.4 beats/min after cows stood and decreased 4.8 +/- 1.0 beats/min after cows lay. Similarly, the average heart rate for the cow naive to the facility increased from 60 to 86 beats/min and remained elevated for 6.3 min when heart rate was indexed to maximal heart rate within +/- 3 min of entry into the pass-through stall. Heart rate for the naive cow increased consistently from around 60 to over 160 beats/min during repeated agonistic encounters between animals. Heart rate for the other cow was not affected by the encounters. These results show clearly that heart rate can be used to monitor animal anxiety.

Aortic pressure estimation with electro-mechanical circulatory assist devices.

An adaptive technique for the estimation of the time history of aortic pressure (from applied voltage and position feedback) has been designed, implemented, and bench tested using the Penn State Electric Ventricular Assist Device (EVAD). This method, known in the field of automatic control as a dynamic observer, utilizes gains which were determined using experimental data collected while the EVAD was running on a mock circulatory system. An adaptive scheme provides the observer with a method of changing its initial conditions on a stroke-by-stroke basis which improves observer performance. In both determining the feedback gains and developing the adaptation scheme, a range of beat rates and pressure loads was taken into account to yield satisfactory observer performance over a range of operating conditions. The observer was implemented, its performance was verified in vitro and results are reported. In the six experimental operating conditions, the beat rate ranged from 56-104 beats per minute (bpm) and the span of the mean systolic aortic pressure was 10.7-18.7 kPa (80-140 mmHg). For these cases, the mean deviation between the actual and estimated aortic pressure during the latter two-thirds of systole was 0.41 kPa (3.1 mmHg).

An optimal controller for an electric ventricular-assist device: theory, implementation, and testing.

This paper addresses the development and testing of an optimal position feedback controller for the Penn State electric ventricular-assist device (EVAD). The control law is designed to minimize the expected value of the EVAD's power consumption for a targeted patient population. The closed-loop control law is implemented on an Intel 8096 microprocessor and in vitro test runs show that this controller improves the EVAD's efficiency by 15-21%, when compared with the performance of the currently used feedforward control scheme.

An adaptive aortic pressure observer for the Penn State Electric Ventricular Assist Device.

This paper addresses the development of an aortic pressure observer for the Penn State Electric Ventricular Assist Device (EVAD). The observer estimates the aortic blood pressure by measuring the voltage of the electric motor and the pusher plate position. The estimated pressure is fedback to the EVAD's blood flow controller, which adjusts the beat rate of the device to accommodate the varying demand of cardiac output. The gains of the observer are deterministically optimized such that the optimal values are independent of the (often unknown) system state initial conditions. To improve the performance of the pressure observer an adaptation scheme is developed. In this scheme the initial pressure estimate of the succeeding systolic cycle is adjusted when the pressure does not match its corresponding second estimated value. In vitro test runs of the developed observer show that is is robust to parameter variations, and the error of the resultant estimated pressure is less than 5%.