the effect of control strategies for an active back support exoskeleton on spine loading and kinematics during lifting with mechanical loading as the main risk factor for lbp exoskeletons exo are designed to reduce the load on the back by taking over part of the moment normally generated by back muscles the present study investigated the effect of an active exoskeleton controlled using three different control modes inclination emg hybrid on spinal compression forces during lifting with various techniques ten healthy male subjects lifted a 15 kg box with three lifting techniques free squat stoop each of which was performed four times once without exo and once each with the three different control modes using inverse dynamics we calculated l5 s1 joint moments subsequently we estimated spine forces using an emg assisted trunk model peak compression forces substantially decreased by 17 8 when wearing the exo compared to no exo however this reduction was partly by about one third attributable to a reduction of 25 in peak lifting speed when wearing the exo while subtle differences in back load patterns were seen between the three control modes no differences in peak compression forces were found in part this may be related to limitations in the torque generating capacity of the exo therefore with the current limitations of the motors it was impossible to determine which of the control modes was best despite these limitations the exo still reduced both peak and cumulative compression forces by about 18

on the stability of functional equations on a square symmetric groupoid abstract let x be a square symmetric groupoid and y d a complete metric divisible square symmetric groupoid in this paper we obtain the hyers ulam stability problem of the functional inequality d g x y g x g y e x y for approximate mapping g x y of the functional equation f x y f x f y differing by e x 2 0 in particular we have investigated the case of f x f y h f x 1 t f y 1 t on some set y

learnability of quantified formulas we consider the following classes of quantified formulas fix a set of basic relations called a basis take conjunctions of these basic relations applied to variables and constants in arbitrary ways finally quantify existentially or universally some of the variables we introduce some conditions on the basis that guarantee efficient learnability furthermore we show that with certain restrictions on the basis the classification is complete we introduce as an intermediate tool a link between this class of quantified formulas and some well studied structures in universal algebra called clones more precisely we prove that the computational complexity of the learnability of these formulas is completely determined by a simple algebraic property of the basis of relations their clone of polymorphisms finally we use this technique to give a simpler proof of the already known dichotomy theorem over boolean domains

hyers ulam stability of functional equations with a square symmetric operation abstract the stability of the functional equation f x y h f x f y x y s is investigated where h is a homogeneous function and is a square symmetric operation on the set s the results presented include and generalize the classical theorem of hyers obtained in 1941 on the stability of the cauchy functional equation

are recruitment patterns of the trunk musculature compatible with a synergy based on the maximization of endurance abstract to verify that maximization of endurance is important among the functional criteria determining trunk muscle activation patterns symmetric and asymmetric exertions were simulated using a detailed model consisting of 114 muscle slips crossing the lumbosacral junction and employing a cost function which maximizes endurance first the question whether meaningful comparisons can be made between activity predictions for individual muscle slips and surface emg data recorded from larger anatomical entities was addressed this was answered affirmatively since activation patterns predicted by a coarse and a middle version of the model in which activation was constrained to be equal within 14 or 32 groups of muscle slips were similar to those predicted with each muscle slip controlled independently median correlation coefficients between activity vectors predicted by the simplified models and the detailed model were 0 88 and 0 97 respectively the coarse model underestimated the endurance capacity by a median of 21 the middle model by only 0 7 second predicted activities within anatomical entities defined at this level of detail were compared to reference data derived from the literature lavender et al 1992 human factors 34 239 247 1992 journal of orthopaedic research 10 691 700 vink et al 1988 electromyography and clinical neurophysiology 28 517 525 the predicted activity patterns of the crector spinae external oblique and rectus abdominis muscles closely resembled the emg patterns r2 0 48 0 99 furthermore the observed distribution of activity between parts of the crector spinae muscle was adequately predicted

on learning read k satisfy j dnf we study the learnability of read k satisfy j rksj dnf formulas these are boolean formulas in disjunctive normal form dnf in which the maximum number of occurrences of a variable is bounded by k and the number of terms satisfied by any assignment is at most j after motivating the investigation of this class of dnf formulas we present an algorithm that for any unknown rksj dnf formula to be learned with high probability finds a logically equivalent dnf formula using the well studied protocol of equivalence and membership queries the algorithm runs in polynomial time for k cdot j o log n over log log n where n is the number of input variables

learning conditional preference networks conditional preference networks cp nets have recently emerged as a popular language capable of representing ordinal preference relations in a compact and structured manner in this paper we investigate the problem of learning cp nets in the well known model of exact identification with equivalence and membership queries the goal is to identify a target preference ordering with a binary valued cp net by interacting with the user through a small number of queries each example supplied by the user or the learner is a preference statement on a pair of outcomes in this model we show that acyclic cp nets are not learnable with equivalence queries alone even if the examples are restricted to swaps for which dominance testing takes linear time by contrast acyclic cp nets are what is called attribute efficiently learnable when both equivalence queries and membership queries are available we indeed provide a learning algorithm whose query complexity is linear in the description size of the target concept but only logarithmic in the total number of attributes interestingly similar properties are derived for tree structured cp nets in the presence of arbitrary examples our learning algorithms are shown to be quasi optimal by deriving lower bounds on the vc dimension of cp nets in a nutshell our results reveal that active queries are required for efficiently learning cp nets in large multi attribute domains

new horn revision algorithms a revision algorithm is a learning algorithm that identifies the target concept starting from an initial concept such an algorithm is considered efficient if its complexity in terms of the measured resource is polynomial in the syntactic distance between the initial and the target concept but only polylogarithmic in the number of variables in the universe we give efficient revision algorithms in the model of learning with equivalence and membership queries the algorithms work in a general revision model where both deletion and addition revision operators are allowed in this model one of the main open problems is the efficient revision of horn formulas two revision algorithms are presented for special cases of this problem for depth 1 acyclic horn formulas and for definite horn formulas with unique heads

lumbar spinal muscle activation synergies predicted by multi criteria cost function the hypothesis that control of lumbar spinal muscle synergies is biomechanically optimized was studied by comparing emg data with an analytical model with a multi component cost function that could include 1 trunk displacements 2 intervertebral displacements 3 intervertebral forces 4 sum of cubed muscle stresses and 5 eigenvalues for the first two spinal buckling modes the model s independent variables were 180 muscle forces the 36 displacements of 6 vertebrae were calculated from muscle forces and the spinal stiffness calculated muscle activation was compared with emg data from 14 healthy human subjects who performed isometric voluntary ramped maximum efforts at angles of 0 degrees 45 degrees 90 degrees 135 degrees and 180 degrees to the right from the anterior direction muscle activation at each angle was quantified as the linear regression slope of the rms emg versus external force relationship normalized by the maximum observed emg there was good agreement between the analytical model and emg data for the dorsal muscles when the model included either minimization of intervertebral displacements or minimization of intervertebral forces in its cost function but the model did not predict a realistic level of abdominal muscles activation agreement with emg data was improved with the sum of the cubed muscle stresses added to the cost function addition of a cost function component to maximize the trunk stability produced higher levels of antagonistic muscle activation at low efforts than at greater efforts it was concluded that the muscle activation strategy efficiently limits intervertebral forces and displacements and that costs of higher muscle stresses are taken into account but stability does not appear to be maximized trunk muscles are apparently not controlled solely to optimize any one of the biomechanical costs considered here

decision tree approximations of boolean functions decision trees are popular representations of boolean functions we show that given an alternative representation of a boolean function f say as a read once branching program one can find a decision tree t which approximates f to any desired amount of accuracy moreover the size of the decision tree is at most that of the smallest decision tree which can represent f and this construction can be obtained in quasi polynomial time we also extend this result to the case where one has access only to a source of random evaluations of the boolean function f instead of a complete representation in this case we show that a similar approximation can be obtained with any specified amount of confidence as opposed to the absolute certainty of the former case this latter result implies proper pac learnability of decision trees under the uniform distribution without using membership queries

muscular synergism ii a minimum fatigue criterion for load sharing between synergistic muscles a new physiological criterion for muscular load sharing is developed the criterion is based on the assumption that the endurance time of muscular contractions is maximized hence muscular fatigue is minimized the optimization problem is cast in the form of a linearly constrained non linear minimax optimization the new method predicts that 1 there is synergistic muscle action 2 muscle force increases non linearly with external force load 3 relatively more force is allocated to muscles that have a large maximum force large muscles 4 relatively more force is allocated to muscles with a high percentage of slow twitch fibers muscles that are fatigue resistant 5 the load sharing does not depend on the moment arm of the muscles although the absolute force levels do depend on this variable the predicted load sharing between two cat muscles during standing and walking is in good agreement with direct force measurement data from the literature

on learning monotone dnf under product distributions we show that the class of monotone 2o logn term dnf formulae can be pac learned in polynomial time under the uniform distribution from random examples only this is an exponential improvement over the best previous polynomial time algorithms in this model which could learn monotone o log2 n term dnf we also show that various classes of small constant depth circuits which compute monotone functions are pac learnable in polynomial time under the uniform distribution all of our results extend to learning under any constant bounded product distribution

on the proper learning of axis parallel concepts we study the proper learnability of axis parallel concept classes in the pac learning and exact learning models these classes include union of boxes dnf decision trees and multivariate polynomials for constant dimensional axis parallel concepts c we show that the following problems have time complexities that are within a polynomial factor of each other c is properly exactly learnable with hypotheses of size at most times the target size from membership and equivalence queries c is properly pac learnable without membership queries under any product distribution there is an approximation algorithm for the minequic problem given a g c find a minimal size f c that is logically equivalent to g in particular if one has polynomial time complexity they all do using this we give the first proper learning algorithm of constant dimensional decision trees and the first negative results in proper learning from membership and equivalence queries for many classes for axis parallel concepts over a nonconstant dimension we show that with the equivalence oracle 1 3 we use this to show that binary decision trees are not properly learnable in polynomial time assuming p np and dnf is not se properly learnable e 1 in polynomial time even with an np oracle assuming 2p pnp

co activation alters the linear versus non linear impression of the emg torque relationship of trunk muscles the use of electromyographic signals in the modeling of muscle forces and joint loads requires an assumption of the relationship between emg and muscle force this relationship has been studied for the trunk musculature and been shown to be predominantly non linear with more emg producing less torque output at higher levels of activation however agonist antagonist muscle co activation is often substantial during trunk exertions yet has not been adequately accounted for in determining such relationships the purpose of this study was to revisit the emg moment relationship of the trunk recognizing the additional moment requirements necessitated due to antagonist muscle activity eight participants generated a series of isometric ramped trunk flexor and extensor moment contractions emg was recorded from 14 torso muscles and the externally resisted moment was calculated agonist muscle moments either flexor or extensor were estimated from an anatomically detailed biomechanical model of the spine and fit to the externally calculated moment alone the externally calculated moment combined with the antagonist muscle moment when antagonist activity was ignored the emg moment relationship was found to be non linear similar to previous work however when accounting for the additional muscle torque generated by the antagonist muscle groups the relationships became in three of the four conditions more linear therefore it was concluded that antagonist muscle co activation must be included when determining the emg moment relationship of trunk muscles and that previous impressions of non linear emg force relationships should be revisited

trunk muscle electromyography and whole body vibration by measuring the electromyographic emg activity of the paraspinal muscles we have estimated the average and peak to peak torque imposed on the spine during whole body vibration six subjects had surface electrodes placed on their erector spinae muscles at the l3 level the emg torque relationship was estimated by having each subject perform isometric horizontal pulls in an upright seated posture the subject was then vibrated vertically and sinusoidally in a controlled flexed slightly lordotic seated posture in 1 hz increments from 3 to 10 hz at a 0 1 g rms seat acceleration level between vibration readings taken at each frequency a static reading was also taken with the subject maintaining the same posture the entire vibration static 3 10 hz test was repeated for reliability purposes specialized digital signal processing techniques were developed for the emg signals to enhance the measured cyclic muscle activity and to allow automatic measurement of the time relationship between the mechanical displacement and the estimated torque we found significantly more average and peak to peak estimated torque at almost all frequencies for vibration vs static sitting

a generalization of the hyers ulam rassias stability of approximately additive mappings abstract in this paper we prove a generalization of the stability of approximately additive mappings in the spirit of hyers ulam and rassias

sensitivity of predicted muscle forces to parameters of the optimization based human leg model revealed by analytical and numerical analyses there are different opinions in the literature on whether the cost functions the sum of muscle stresses squared and the sum of muscle stresses cubed can reasonably predict muscle forces in humans one potential reason for the discrepancy in the results could be that different authors use different sets of model parameters which could substantially affect forces predicted by optimization based models in this study the sensitivity of the optimal solution obtained by minimizing the above cost functions for a planar three degrees of freedom dof model of the leg with nine muscles was investigated analytically for the quadratic function and numerically for the cubic function analytical results revealed that generally the non zero optimal force of each muscle depends in a very complex non linear way on moments at all three joints and moment arms and physiological cross sectional areas pcsas of all muscles deviations of the model parameters moment arms and pcsas from their nominal values within a physiologically feasible range affected not only the magnitude of the forces predicted by both criteria but also the number of non zero forces in the optimal solution and the combination of muscles with non zero predicted forces muscle force magnitudes calculated by both criteria were similar they could change several times as model parameters changed whereas patterns of muscle forces were typically not as sensitive it is concluded that different opinions in the literature about the behavior of optimization based models can be potentially explained by differences in employed model parameters

conjunctions of unate dnf formulas learning and structure abstract a central topic in query learning is to determine which classes of boolean formulas are efficiently learnable with membership and equivalence queries we consider the class r kconsisting of conjunctions ofkunate dnf formulas this class generalizes the class ofk clause cnf formulas and the class of unate dnf formulas both of which are known to be learnable in polynomial time with membership and equivalence queries we prove that r 2can be properly learned with a polynomial number of polynomial size membership and equivalence queries but can be properly learned in polynomial time with such queries if and only if p np thus the barrier to properly learning r 2with membership and equivalence queries is computational rather than informational few results of this type are known in our proofs we use recent results of hellersteinet al 1997 j assoc comput mach 43 5 840 862 characterizing the classes that are polynomial query learnable together with work of bshouty on the monotone dimension of boolean functions we extend some of our results to r kand pose open questions on learning dnf formulas of small monotone dimension we also prove structural results for r k we construct for any fixedk 2 a class of functionsfthat cannot be represented by any formula in r k but which cannot be easily shown to have this property more precisely for any functionfonnvariables in the class the value offon any polynomial size set of points in its domain is not a witness thatfcannot be represented by a formula in r k our construction is based on bch codes

effects of asymmetric load carrying on the biomechanics of walking abstract the purpose of the study was to investigate the effects of an asymmetric sidepack carrying system on frontal plane joint moments of force in both lower extremities and in the l5 s1 joint during level walking ground reaction force data and frontal plane film records were obtained from five males performing three walking conditions 0 10 and 20 bodyweight loads in a sidepack supported by the left shoulder inverse dynamics were used to calculate the lower extremity moments during stance and a static model of the pelvis was used to calculate the l5 s1 moments during single support for each limb normal walking was characterized by symmetric kinetics between left and right limbs and around the l5 s1 joint the asymmetric loads produced unbalanced lateral trunk muscle dominance between left and right limb stance phases increased right hip and knee moments and decreased left hip and knee moments during normal walking the l5 s1 moment was dominant on the contralateral trunk side for both limbs the asymmetric loads applied to the left side caused a shift in l5 s1 moment dominance to the right side during left and right single support phases

exact learning boolean functions via the monotone theory we study the learnability of boolean functions from membership and equivalence queries we develop the monotone theory that proves 1 any boolean function is learnable in polynomial time in its minimal disjunctive normal form size its minimal conjunctive normal form size and the number of variables n in particular 2 decision trees are learnable our algorithms are in the model of exact learning with membership queries and unrestricted equivalence queries the hypotheses to the equivalence queries and the output hypotheses are depth 3 formulas

an emg assisted model of trunk loading during free dynamic lifting abstract one of the continuing challenges in biomechanics has been to assess loading of the spine during dynamic lifting exertions a model was developed to accurately simulate multi dimensional spinal loads and trunk moments from measured muscle coactivity and external forces during free dynamic lifting exertions model validity was demonstrated by comparing measured and predicted trunk extension moments its purpose was to examine realistic representations of lifting kinetics kinematics and dynamic trunk mechanics that may influence spinal loading and to demonstrate that emg assisted modeling techniques can be applied to the analysis of free dynamic exertions spinal loads and trunk moments were predicted from the muscle force vectors and external loads muscle tensile forces were determined from the product of normalized emg data modulated to account for contractile dynamics muscle cross sectional area and muscle force per unit cross sectional area model output was physiologically valid i e average predicted muscle force per unit cross sectional area of 50 65 n cm 2 and accurately predicted measured dynamic lifting moments with an average r 2 0 81 in the sagittal plane and r 2 0 76 in the lateral plane results indicated that compressive and shear loading increased significantly with exertion load lifting velocity and trunk asymmetry

learning random log depth decision trees under uniform distribution we consider three natural models of random logarithmic depth decision trees over boolean variables we give an efficient algorithm that for each of these models learns all but an inverse polynomial fraction of such trees using only uniformly distributed random examples from 0 1 n the learning algorithm constructs a decision tree as its hypothesis

theory revision with queries horn read once and parity formulas a theory in this context is a boolean formula it is used to classify instances or truth assignments theories can model real world phenomena and can do so more or less correctly the theory revision or concept revision problem is to correct a given roughly correct concept this problem is considered here in the model of learning with equivalence and membership queries a revision algorithm is considered efficient if the number of queries it makes is polynomial in the revision distance between the initial theory and the target theory and polylogarithmic in the number of variables and the size of the initial theory the revision distance is the minimal number of syntactic revision operations such as the deletion or addition of literals needed to obtain the target theory from the initial theory efficient revision algorithms are given for horn formulas and read once formulas where revision operators are restricted to deletions of variables or clauses and for parity formulas where revision operators include both deletions and additions of variables we also show that the query complexity of the read once revision algorithm is near optimal

precision of estimates of mean and peak spinal loads in lifting a bootstrap procedure was used to determine the statistical precision of estimates of mean and peak spinal loads during lifting as function of the numbers of subjects and measurements per subject included in a biomechanical study data were derived from an experiment in which 10 subjects performed 360 lifting trials each the maximum values per lift of the lumbar flexion angle l5s1 sagittal plane moment and l5s1 compression force were determined from the data set thus compiled 3000 samples were randomly drawn for each combination of number of subjects and number of measurements considered the coefficients of variation of mean and peak defined as mean plus 2 standard deviations spinal loads across these samples were calculated the coefficients of variation of the means of the three parameters of spinal load decreased as a linear function of the number of subjects to a power of about 0 48 and number of measurements to a power of about 0 06 while the corresponding powers for peak loads were about 0 44 and 0 11

the relationship between trunk muscle electromyography and lifting moments in the sagittal and frontal planes in this study we explore the relationship between moments in the frontal and sagittal planes generated by a lifting task vs the electromyographic emg activity of right and left trunk muscle groups in particular we postulate that the functional dependence between erector spinae muscle activity and the applied lifting moments about the spine is as follows 1 the sum of left and right erector spinae processed emg depends on the sagittal plane moment and 2 the difference of left and right erector spinae processed emg depends on the frontal plane moment a simple out of sagittal plane physical model treating the lumbar spine as a two degree of freedom pivot point is discussed to justify these hypotheses to validate this model we collected surface emg and lifting moment data for ten males performing a grid of frontal and sagittal plane lifting tasks a digital rms to dc algorithm was developed for processing raw emg for these tests we measured emg for the left and right erector spinae and for the left and right external oblique muscles the processed emg signals of the left and right erector spinae muscles are summed and differenced for comparison to the measured sagittal and frontal plane moments a linear correlation r2 of 0 96 was obtained for the sum of erector spinae emg vs the sagittal plane moment a corresponding value of r2 0 95 was obtained for the difference vs the frontal plane moment no correlations r2 0 004 was found for 1 the sagittal plane moment and the difference of the left and right erector spinae emg and 2 the frontal plane moment and the sum of the left and right erector spinae emg

sensitivity of single equivalent trunk extensor muscle models to anatomical and functional assumptions single equivalent muscle models are often used to estimate loads on the lumbosacral joint after net extension moments have been calculated by means of inverse dynamics these models usually ignore the effects trunk flexion has on the extensor lever arm in addition no systematic analysis of the sensitivity to the anatomical and functional assumptions made in these models is available in the present study a series of single equivalent models incorporating trunk flexion dependence was derived from a detailed description of the trunk musculature each model was based on different anatomical and functional assumptions the differences of estimates of compression and shear forces on the lumbosacral disc during a lifting movement resulting from these models were analysed the results show that these load estimates heavily depend on assumptions regarding anthropometry lumbar curvature and coactivity of abdominal muscles and only moderately on assumptions regarding force sharing between extensor muscles fairly simple single equivalent models with the net moment and thorax orientation as input can be used to predict lumbosacral compression and shear

a physiologically based criterion of muscle force prediction in locomotion abstract the inversely nonlinear relationship of muscle contraction force and the possible contraction duration i e endurance is utilized in a method to mathematically predict individual muscle forces the method uses a nonlinear optimization scheme to solve the redundant distribution problem at the joints of interest the method is demonstrated at the elbow during isometric contraction and in the lower extremity during locomotion during gait the observed muscle activity pattern in the lower extremity as determined by emg shows substantial agreement with that activity pattern predicted when endurance is used as the optimization criterion the importance of selecting muscle prediction criteria based on sound physiological bases rather than on an arbitrary or mathematically convenient basis is emphasized

lifting over an obstacle effects of one handed lifting and hand support on trunk kinematics and low back loading abstract mechanical loading of the low back during lifting is a common cause of low back pain in this study two handed lifting is compared to one handed lifting with and without supporting the upper body with the free hand while lifting over an obstacle a 3 d linked segment model was combined with an emg assisted trunk muscle model to quantify kinematics and joint loads at the l5s1 joint peak total net moments i e the net moment effect of all muscles and soft tissue spanning the joint were found to be 10 3 lower in unsupported one handed lifting compared to two handed lifting and 30 8 lower in supported compared to unsupported one handed lifting l5s1 joint forces also showed reductions but not of the same magnitude 18 8 and 15 10 respectively for compression forces and 15 17 and 11 14 respectively for shear forces those reductions of low back load were mainly caused by a reduction of trunk and load moment arms relative to the l5s1 joint during peak loading and in the case of hand support by a support force of about 250 n stretching one leg backward did not further reduce low back load estimates furthermore one handed lifting caused an 6 8 increase in lateral flexion a 9 5 increase in twist and a 6 6 decrease in flexion support with the free hand caused a small further increase in lumbar twisting it is concluded that one handed lifting especially with hand support reduces l5s1 loading but increases asymmetry in movements and moments about the lumbar spine

variations on extending partially defined boolean functions with missing bits in this paper we consider four possible definitions for extending a partially defined boolean function in which the input contains some missing bits we show somewhat surprisingly that for many general and frequently used families of function classes three of these notions of an extension are mathematically equivalent though such an equivalence does not hold universally as demonstrated by several examples

on computing all abductive explanations from a propositional horn theory abduction is a fundamental mode of reasoning with applications in many areas of ai and computer science the computation of abductive explanations is an important computational problem which is at the core of early systems such as the atms and clause management systems and is intimately related to prime implicate generation in propositional logic many algorithms have been devised for computing some abductive explanation and the complexity of the problem has been well studied however little attention has been paid to the problem of computing multiple explanations and in particular all explanations for an abductive query we fill this gap and consider the computation of all explanations of an abductive query from a propositional horn theory or of a polynomial subset of them our study pays particular attention to the form of the query ranging from a literal to a compound formula to whether explanations are based on a set of abducible literals and to the representation of the horn theory either by a horn conjunctive normal form cnf or model based in terms of its characteristic models for these combinations we present either tractability results in terms of polynomial total time algorithms intractability results in terms of nonexistence of such algorithms unless p e np or semi tractability results in terms of solvability in quasi polynomial time established by polynomial time equivalence to the problem of dualizing a monotone cnf expression our results complement previous results in the literature and refute a longstanding conjecture by selman and levesque they elucidate the complexity of generating all abductive explanations and shed light on related problems such as generating sets of restricted prime implicates of a horn theory the algorithms for tractable cases can be readily applied for generating a polynomial subset of explanations in polynomial time

effects of emg processing on biomechanical models of muscle joint systems sensitivity of trunk muscle moments spinal forces and stability biomechanical models are in use to estimate parameters such as contact forces and stability at various joints in one class of these models surface electromyography emg is used to address the problem of mechanical indeterminacy such that individual muscle activation patterns are accounted for unfortunately because of the stochastical properties of emg signals emg based estimates of muscle force suffer from substantial estimation errors recent studies have shown that improvements in muscle force estimation can be achieved through adequate emg processing specifically whitening and high pass hp filtering of the signals the aim of this paper is to determine the effect of such processing on outcomes of a biomechanical model of the lumbosacral joint and surrounding musculature goodness of fit of estimated muscle moments to net moments and also estimated joint stability significantly increased with increasing cut off frequencies in hp filtering whereas no effect on joint contact forces was found whitening resulted in moment estimations comparable to those obtained from optimal hp filtering with cut off frequencies over 250 hz moreover compared to hp filtering whitening led to a further increase in estimated joint stability based on theoretical models and on our experimental results we hypothesize that the processing leads to an increase in pick up area this then would explain the improvements from a better balance between deep and superficial motor unit contributions to the signal

learning from examples with unspecified attribute values a challenging problem within machine learning is how to make good inferences from data sets in which pieces of information are missing while it is valuable to have algorithms that perform well for specific domains to gain a fundamental understanding of the problem one needs a theory about how to learn with incomplete data the important contribution of such a theory is not so much the specific algorithmic results but rather that it provides good ways of thinking about the problem formally in this paper we introduce the unspecified attribute value uav learning model as a first step towards a theoretical framework for studying the problem of learning from incomplete data in the exact learning framework in the uav learning model an example x is classified positive resp negative if all possible assignments for the unspecified attributes result in a positive resp negative classification otherwise the classification given to x is for unknown given an example x in which some attributes are unspecified the oracle uav mq responds with the classification of x given a hypothesis h the oracle uav eq returns an example x that could have unspecified attributes for which h x is incorrect we show that any class of functions learnable in angluin s exact model using the mq and eq oracles is also learnable in the uav model using the mq and uav eq oracles as long as the counterexamples provided by the uav eq oracle have a logarithmic number of unspecified attributes we also show that any class learnable in the exact model using the mq and eq oracles is also learnable in the uav model using the uav mq and uav eq oracles as well as an oracle to evaluate a given boolean formula on an example with unspecified attributes for some hypothesis classes such as decision trees and unate formulas the evaluation can be done in polynomial time without an oracle we also study the learnability of a universal class of decision trees under the uav model and of dnf formulas under a representation dependent variation of the uav model

subject specific regression equations to estimate lower spinal loads during symmetric and asymmetric static lifting abstract workplace safety assessment personalized treatment design and back pain prevention programs require accurate subject specific estimation of spinal loads since no noninvasive method can directly estimate spinal loads easy to use regression equations that are constructed based on the results of complex musculoskeletal models appear as viable alternatives thus we aim to develop subject specific regression equations of l4 l5 and l5 s1 shear and compression forces during various symmetric asymmetric tasks using a nonlinear personalized finite element musculoskeletal trunk model kinematics and electromyography emg activities of 19 young healthy subjects were collected during 64 different symmetric asymmetric tasks to investigate the reliability and accuracy of the musculoskeletal model and regression equations we compared estimated trunk muscle activities and l4 l5 intradiscal pressures idps respectively with our own electromyography data emgs and reported in vivo pressure measurements although in general six independent rotation components three trunk t11 rotations and three pelvic s1 rotations are required to determine kinematics along the spine only two surrogate variables trunk flexion and its asymmetric angles satisfactorily predicted all six rotation components r2 0 94 regression equations developed based on subject specific inputs predicted spinal loads in satisfactory agreement with idp measurements r2 0 85 predicted muscle activities in the personalized musculoskeletal models were in moderate to weak agreements with our measured emgs in 19 participants based on dominance analysis trunk flexion and its asymmetry angle hand load weight hand load lever arm and body weight were the most important variables while the effects of body height and sex on spinal loads remained small

the mechanics of back extensor torque production about the lumbar spine the purpose of this study was to develop and evaluate a biomechanical model of lumbar back extension over a wide range of positions for the lumbar spine incorporating the latest information on muscle geometry and intra abdominal pressure iap analysis of the visible human data was utilised in order to obtain anatomical information unavailable from the literature and magnetic resonance imaging was used to generate subject specific anatomical descriptions the model was evaluated by comparisons with measured maximal voluntary static back extension torques predicted maximal specific muscle tensions agreed well with in vitro measurements from the literature when modelling the maximal static back extension torque production it was possible to come fairly close to simultaneous equilibrium about all the lumbar discs simply by a uniform muscle activation of all back extensor muscles the caudal part showed however less agreement this indicates that equilibrium in the lumbar spine is mainly regulated by passive mechanical properties e g muscle length changes due to postural changes rather than due to complex muscle coordination as earlier proposed the model showed that iap measured during torque exertions contributes about 10 of the total maximal voluntary back extensor torque and that it can unload the spine from compression the spinal unloading effect from the iap was greatest with the spine held in a flexed position this is in opposition to the effects of changed muscle lever arm lengths which for a given load would give the largest spinal unloading in the extended position these findings have implications for the evaluation of optimal lifting techniques

the monotone theory for the pac model in this paper we extend the monotone theory to the pac learning model with membership queries using this extention we show that a dnf formula that has at least one 1 poly heavy clause in one of its cnf representation a clause that is not satisfied with probability 1 poly n s where n is the number of variables and s is the number of terms in f with respect to a distribution d is weakly learnable under this distribution so dnf that are not weakly learnable under the distribution d do not have any 1 poly heavy clauses in any of their cnf representations a dnf f is called cdnf if there is and a cnf representation of f that contains poly n s clauses that approximates f according to a distribution d we show that the class of all cdnf is weakly e pac learnable with membership queries under the distribution d we then show how to change our algorithm to a parallel algorithm that runs in polylogarithmic time with a polynomial number of processors in particular decision trees are strongly pac learnable with membership queries under any distribution in parallel in polylogarithmic time with a polynomial number of processors finally we show that no efficient parallel exact learning algorithm exists for decision trees

learning functions represented as multiplicity automata we study the learnability of multiplicity automata in angluin s exact learning model and we investigate its applications our starting point is a known theorem from automata theory relating the number of states in a minimal multiplicity automaton for a function to the rank of its hankel matrix with this theorem in hand we present a new simple algorithm for learning multiplicity automata with improved time and query complexity and we prove the learnability of various concept classes these include among others the class of disjoint dnf and more generally satisfy o 1 dnf the class of polynomials over finite fields the class of bounded degree polynomials over infinite fields the class of xor of terms certain classes of boxes in high dimensions in addition we obtain the best query complexity for several classes known to be learnable by other methods such as decision trees and polynomials over gf 2 while multiplicity automata are shown to be useful to prove the learnability of some subclasses of dnf formulae and various other classes we study the limitations of this method we prove that this method cannot be used to resolve the learnability of some other open problems such as the learnability of general dnf formulas or even k term dnf for k log n or satisfy s dnf formulas for s 1 these results are proven by exhibiting functions in the above classes that require multiplicity automata with super polynomial number of states

comparison of muscle forces and joint load from an optimization and emg assisted lumbar spine model towards development of a hybrid approach abstract the purpose of this study was to determine whether the same estimates of individual muscle and l4 l5 lumbar joint compressive forces result from an optimization opt compared to an electromyography emg assisted approach for solving the inderminate moment equilibrium equations in the same anatomical model four male subjects performed near maximum isometric ramp efforts in trunck flexion extension and lateral bending in a testing apparatus the emg approach was sensitive to subject and trial differences in the magnitudes of individual muscle forces needed to produce the same reaction moment in contrast the opt method converged on a similar estimate of muscle forces for all subjects and trials producing the same moment the opt method predicted lower l4 l5 joint compression values on average by 32 43 and 23 in trunk extension flexion and lateral bending respectively because unlike the emg method it could not predict co contraction of anatomically antagonistic muscles we incorporated the opt method s advantage of forcing an equilibrium in the reaction moments into the emg method in a new approach we have called emg assisted optimization emgao muscle force estimates from the emg and emgao methods differed from those from the opt method on average by 123 rms for flexion and extension and by 218 for lateral bends data from the two approaches result in different conclusions about spine mechanics we have more confidence in the emg assisted methods because they respond to variation in muscle synergy and co contraction patterns commonly observed in different trials and subjects for the same reaction moments

an explicit expression for the moment in multibody systems the equations of motion are formulated for a set of interacting rigid bodies an explicit formulation could be derived for the total moment of the forces on such a system this is applied to 1 the intersegmental moment in a multisegment rigid body model and 2 the interpretation of the centre of pressure as defined in the studies of human posture