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Objective:In this cohort of individuals with and without multiple sclerosis (MS), we illustrate some of the novel approaches that smartphones provide to monitor patients with chronic neurologic disorders in their natural setting.Methods:Thirty-eight participant pairs (MS and cohabitant) aged 18–55 years participated in the study. Each participant received an Android HTC Sensation 4G smartphone containing a custom application suite of 19 tests capturing participant performance and patient-reported outcomes (PROs). Over 1 year, participants were prompted daily to complete one assigned test.Results:A total of 22 patients with MS and 17 cohabitants completed the entire study. Among patients with MS, low scores on PROs relating to mental and visual function were associated with dropout (p < 0.05). We illustrate several novel features of a smartphone platform. First, fluctuations in MS outcomes (e.g., fatigue) were assessed against an individual's ambient environment by linking responses to meteorological data. Second, both response accuracy and speed for the Ishihara color vision test were captured, highlighting the benefits of both active and passive data collection. Third, a new trait, a person-specific learning curve in neuropsychological testing, was identified using spline analysis. Finally, averaging repeated measures over the study yielded the most robust correlation matrix of the different outcome measures.Conclusions:We report the feasibility of, and barriers to, deploying a smartphone platform to gather useful passive and active performance data at high frequency in an unstructured manner in the field. A smartphone platform may therefore enable large-scale naturalistic studies of patients with MS or other neurologic diseases.

Speaker recognition refers to the concept of recognizing a speaker by his=her voice or speech samples. Some of the important applications of speaker recognition include customer veriÿcation for bank transactions, access to bank accounts through telephones, control on the use of credit cards, and for security purposes in the army, navy and airforce. This paper is purely a tutorial that presents a review of the classiÿer based methods used for speaker recognition. Both unsupervised and supervised classiÿers are described. In addition, practical approaches that utilize diversity, redundancy and fusion strategies are discussed with the aim of improving performance.

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Prediction error filters which combine short-time prediction (formant prediction) with long-time prediction (pitch prediction) in a cascade connection are examined. A number of different solution methods (autocorrelation, covariance, Burg) and implementations (transversal and lattice) are considered. It is found that the F-P cascade (formant filter before the pitch filter) outperforms the P-F cascade for both transversal-and lattice-structured predictors. The performances of the transversal and lattice forms are similar. The solution method that yields a transversal structure requires a stability test and, if necessary, a consequent stabilization. The lattice form allows for a solution method which ensures a stable synthesis filter. Simplified solution methods are shown to be applicable for the pitch filter (multitap case) in an F-P cascade. Furthermore, new methods to estimate the appropriate pitch lag for a pitch filter are proposed for both transversal and lattice structures. These methods perform essentially as well as an exhaustive search in an F-P cascade. Finally, the two cascade forms are implemented as part of an APC coder to evaluate their relative subjective performance. ' 1n our limited experiments with pitch filters derived using an autocorrelation formulation, no instability was observed.

We report the outcome of a prospective consecutive series of 52 primary total hip arthroplasties using the miniature porous-coated Anatomic Medullary Locking stem in patients with small anatomic proportions because of hip dysplasia or juvenile chronic arthritis. The mean age of the patients at the time of surgery was 28.7 years (range 14-56 years). The average body weight and height of the patients were 51.8 kg (range 38.5-78.3 kg) and 157.1 cm (range 142.2-183 cm), respectively. The stem was cementless in 40 hips and cemented in 12 hips because of poor bone stock. A cementless acetabular cup with screw was used in all hips. The average followup was 7.1 years (range, 3-15.6 years). The Harris hip scores improved from an average of 31.2 points (range, 3.1-68.8 points)preoperatively to 82.8 points (range, 61.1-96.6 points) at latest followup. Three of 12 (25%) cemented and two of 40 (5%) cementless stem were revised. Four of seven 42-44-mm cups were revised. The miniature Anatomic Medullary Locking cementless femoral stem provides a satisfactory outcome in patients with small anatomic proportions. However, wear and osteolysis with the use of a small cementless polyethylene liner remain challenges.