Is SEMG recorded “hyperactivity” during mandibular rest a sign of dysfunctional jaw muscle activity and temporomandibular disorders (TMD)?

BackgroundSome authors state that above‐normal surface electromyography (SEMG) levels during mandibular rest (MR) are a general sign of temporomandibular disorders (TMD).ObjectiveThe aim was to compare SEMG levels in the masseter and anterior temporalis areas during MR between patients with disc displacement (DD) and subjects identified as healthy. The hypothesis was that average SEMG levels would be higher in the patients during MR before and after repeated clenches with maximal effort.MethodsThirty‐six healthy subjects, and 42 patients with DD, were included. SEMG levels were recorded bilaterally in the temporalis and masseter areas during MR before clenching and after repeated clenches with maximal effort. Multivariate analysis of variance (MANOVA) was used to compare the means of the log‐transformed SEMG‐values for the subject groups.ResultsThe mean MR levels in the four areas before clenching ranged from −0.19 log (µV) to 1.20 log(µV) in healthy subjects and from −0.22 log(µV) to 0.96 log(µV) in patients. The mean MR levels in the four areas after repeated clenches ranged from −0.19 log (µV) to 1.04 log(µV) in healthy subjects and from −0.27 log(µV) to 0.93 log(µV) in patients. The MANOVA test showed no significant differences in the means for MR for the four areas between the groups at the 5% significance level.ConclusionThe hypothesis that jaw muscle SEMG levels during MR are on average generally higher in TMD patients is not supported. A possible explanation for the previous findings is that activity in other muscles was mislabelled as jaw muscle activity.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/156203/2/joor13032_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/156203/1/joor13032.pd

Constant Curvature Curve Tube Codes for Low-Latency Analog Error Correction

Recent research in ultra-reliable and low latency communications (URLLC) for future wireless systems has spurred interest in short block-length codes. In this context, we introduce a new class of high-dimension constant curvature curves codes for analog error correction of independent continuous-alphabet uniform sources. In particular, we employ the circumradius function from knot theory to prescribe insulating tubes about the centerline of constant curvature curves. We then use tube packing density within a hypersphere to optimize the curve parameters. The resulting constant curvature curve tube (C3T) codes possess the smallest possible latency -- block-length is unity under bandwidth expansion mapping. Further, the codes provide within $5$ dB of Shannon's optimal performance theoretically achievable at the lower range of signal-to-noise ratios and BW expansion factors. We exploit the fact that the C3T encoder locus is a geodesic on a flat torus in even dimensions and a generalized helix in odd dimensions to obtain useful code properties and provide noise-reducing projections at the decoder stage. We validate the performance of these codes using fully connected multi-layer perceptrons that approximate maximum likelihood decoders. For the case of independent and identically distributed uniform sources, we show that analog error correction is advantageous over digital coding in terms of required block-lengths needed to match {signal-to-noise ratio, source-to-distortion ratio} tuples. The best possible digital codes require two to three orders of magnitude higher latency compared to C3T codes, thereby demonstrating the latter's utility for URLLC.Comment: 11 pages, 2 tables, 6 figure

A multiple motion sensors index for motor state quantification in Parkinson\u27s disease

Aim: To construct a Treatment Response Index from Multiple Sensors (TRIMS) for quantification of motor state in patients with Parkinson\u27s disease (PD) during a single levodopa dose. Another aim was to compare TRIMS to sensor indexes derived from individual motor tasks. Method: Nineteen PD patients performed three motor tests including leg agility, pronation-supination movement of hands, and walking in a clinic while wearing inertial measurement unit sensors on their wrists and ankles. They performed the tests repeatedly before and after taking 150% of their individual oral levodopa-carbidopa equivalent morning dose.Three neurologists blinded to treatment status, viewed patients’ videos and rated their motor symptoms, dyskinesia, overall motor state based on selected items of Unified PD Rating Scale (UPDRS) part III, Dyskinesia scale, and Treatment Response Scale (TRS). To build TRIMS, out of initially 178 extracted features from upper- and lower-limbs data, 39 features were selected by stepwise regression method and were used as input to support vector machines to be mapped to mean reference TRS scores using 10-fold cross-validation method. Test-retest reliability, responsiveness to medication, and correlation to TRS as well as other UPDRS items were evaluated for TRIMS. Results: The correlation of TRIMS with TRS was 0.93. TRIMS had good test-retest reliability (ICC = 0.83). Responsiveness of the TRIMS to medication was good compared to TRS indicating its power in capturing the treatment effects. TRIMS was highly correlated to dyskinesia (R = 0.85), bradykinesia (R = 0.84) and gait (R = 0.79) UPDRS items. Correlation of sensor index from the upper-limb to TRS was 0.89. Conclusion: Using the fusion of upper- and lower-limbs sensor data to construct TRIMS provided accurate PD motor states estimation and responsive to treatment. In addition, quantification of upper-limb sensor data during walking test provided strong results