Circadian blood pressure variation after acute stroke

We aimed to characterise the patterns of circadian blood pressure (BP) variation after acute stroke and determine whether any relationship exists between these patterns and stroke outcome. BP was recorded manually every 4 h for 48 h following acute stroke. Patients were classified according to the percentage fall in mean systolic BP (SBP) at night compared to during the day as: dippers (fall >= 10-= 20%); non-dippers (>= 0-

Computational methods for the detection of facial palsy

We are developing a telemedicine application which offers automated diagnosis of facial (Bell's) palsy through a Web service. We used a test data set of 43 images of facial palsy patients and 44 normal people to develop the automatic recognition algorithm. Three different image pre-processing methods were used. Machine learning techniques (support vector machine, SVM) were used to examine the difference between the two halves of the face. If there was a sufficient difference, then the SVM recognized facial palsy. Otherwise, if the halves were roughly symmetrical, the SVM classified the image as normal. It was found that the facial palsy images had a greater Hamming Distance than the normal images, indicating greater asymmetry. The median distance in the normal group was 331 (interquartile range 277-435) and the median distance in the facial palsy group was 509 (interquartile range 334-703). This difference was significant (P

Motor unit number estimation - A Bayesian approach

All muscle contractions are dependent on the functioning of motor units. In diseases such as amyotrophic lateral sclerosis (ALS), progressive loss of motor units leads to gradual paralysis. A major difficulty in the search for a treatment for these diseases has been the lack of a reliable measure of disease progression. One possible measure would be an estimate of the number of surviving motor units. Despite over 30 years of motor unit number estimation (MUNE), all proposed methods have been met with practical and theoretical objections. Our aim is to develop a method of MUNE that overcomes these objections. We record the compound muscle action potential (CMAP) from a selected muscle in response to a graded electrical stimulation applied to the nerve. As the stimulus increases, the threshold of each motor unit is exceeded, and the size of the CMAP increases until a maximum response is obtained. However, the threshold potential required to excite an axon is not a precise value but fluctuates over a small range leading to probabilistic activation of motor units in response to a given stimulus. When the threshold ranges of motor units overlap, there may be alternation where the number of motor units that fire in response to the stimulus is variable. This means that increments in the value of the CMAP correspond to the firing of different combinations of motor units. At a fixed stimulus, variability in the CMAP, measured as variance, can be used to conduct MUNE using the "statistical" or the "Poisson" method. However, this method relies on the assumptions that the numbers of motor units that are firing probabilistically have the Poisson distribution and that all single motor unit action potentials (MUAP) have a fixed and identical size. These assumptions are not necessarily correct. We propose to develop a Bayesian statistical methodology to analyze electrophysiological data to provide an estimate of motor unit numbers. Our method of MUNE incorporates the variability of the threshold, the variability between and within single MUAPs, and baseline variability. Our model not only gives the most probable number of motor units but also provides information about both the population of units and individual units. We use Markov chain Monte Carlo to obtain information about the characteristics of individual motor units and about the population of motor units and the Bayesian information criterion for MUNE. We test our method of MUNE on three subjects. Our method provides a reproducible estimate for a patient with stable but severe ALS. In a serial study, we demonstrate a decline in the number of motor unit numbers with a patient with rapidly advancing disease. Finally, with our last patient, we show that our method has the capacity to estimate a larger number of motor units.

A pathology of the animal spirits - the clinical neurology of Thomas Willis (1621-1675) Part I - Background, and disorders of intrinsically normal animal spirits

Thomas Willis (1621-1675), author of the classical work Cerebri Anatome (1664), was arguably the father of the modem era of neurology. As compared with his neuroanatomy, relatively little attention has been paid to Willis' clinical neurology, as described in his Pathologiae Cerebri (1667) and Do Anima Brutorum (1672), where he gave a structured account of disease of the nervous system as it was known in his day. His account was largely derived from personal observations and not from traditional authorities and was based around his concept of the animal spirits, a fictitious entity in many ways analogous to the present day idea of the nerve impulse. This concept allowed him to develop a pathology of the animal spirits which embraced the whole content of the clinical neurology and psychiatry of his times. The anatomical and physiological background to Willis! concepts of animal spirit dysfunction, and those disorders he regarded as due to disturbed function of intrinsically normal animal spirits (mainly headache, disorders of consciousness, apoplexy and palsy) are dealt with in the present paper. The disorders he attributed to inherently abnormal animal spirits are considered in a second part of the paper. (C) 2002 Elsevier Science Ltd. All eights reserved.