873 research outputs found
Estimation of musculotendon parameters for scaled and subject specific musculoskeletal models using an optimization technique.
A challenging aspect of subject specific musculoskeletal modeling is the estimation of muscle parameters, especially optimal fiber length and tendon slack length. In this study, the method for scaling musculotendon parameters published by Winby et al. (2008), J. Biomech. 41, 1682-1688, has been reformulated, generalized and applied to two cases of practical interest: 1) the adjustment of muscle parameters in the entire lower limb following linear scaling of a generic model and 2) their estimation "from scratch" in a subject specific model of the hip joint created from medical images. In the first case, the procedure maintained the muscles׳ operating range between models with mean errors below 2.3% of the reference model normalized fiber length value. In the second case, a subject specific model of the hip joint was created using segmented bone geometries and muscle volumes publicly available for a cadaveric specimen from the Living Human Digital Library (LHDL). Estimated optimal fiber lengths were found to be consistent with those of a previously published dataset for all 27 considered muscle bundles except gracilis. However, computed tendon slack lengths differed from tendon lengths measured in the LHDL cadaver, suggesting that tendon slack length should be determined via optimization in subject-specific applications. Overall, the presented methodology could adjust the parameters of a scaled model and enabled the estimation of muscle parameters in newly created subject specific models. All data used in the analyses are of public domain and a tool implementing the algorithm is available at https://simtk.org/home/opt_muscle_par
Effects of hip joint centre mislocation on gait kinematics of children with cerebral palsy calculated using patient-specific direct and inverse kinematic models
Joint kinematics can be calculated by Direct Kinematics (DK), which is used in most clinical gait laboratories, or Inverse Kinematics (IK), which is mainly used for musculoskeletal research. In both approaches, joint centre locations are required to compute joint angles. The hip joint centre (HJC) in DK models can be estimated using predictive or functional methods, while in IK models can be obtained by scaling generic models. The aim of the current study was to systematically investigate the impact of HJC location errors on lower limb joint kinematics of a clinical population using DK and IK approaches. Subject-specific kinematic models of eight children with cerebral palsy were built from magnetic resonance images and used as reference models. HJC was then perturbed in 6mm steps within a 60mm cubic grid, and kinematic waveforms were calculated for the reference and perturbed models. HJC perturbations affected only hip and knee joint kinematics in a DK framework, but all joint angles were affected when using IK. In the DK model, joint constraints increased the sensitivity of joint range-of-motion to HJC location errors. Mean joint angle offsets larger than 5° were observed for both approaches (DK and IK), which were larger than previously reported for healthy adults. In the absence of medical images to identify the HJC, predictive or functional methods with small errors in anterior-posterior and medial-lateral directions and scaling procedures minimizing HJC location errors in the anterior-posterior direction should be chosen to minimize the impact on joint kinematics
Biofeedback for gait retraining based on real-time estimation of tibiofemoral joint contact forces
Biofeedback assisted rehabilitation and intervention technologies have the potential to modify clinically relevant biomechanics. Gait retraining has been used to reduce the knee adduction moment, a surrogate of medial tibiofemoral joint loading often used in knee osteoarthritis research. In this study we present an electromyogram-driven neuromusculoskeletal model of the lower-limb to estimate, in real-time, the tibiofemoral joint loads. The model included 34 musculotendon units spanning the hip, knee, and ankle joints. Full-body inverse kinematics, inverse dynamics, and musculotendon kinematics were solved in real-time from motion capture and force plate data to estimate the knee medial tibiofemoral contact force (MTFF). We analyzed 5 healthy subjects while they were walking on an instrumented treadmill with visual biofeedback of their MTFF. Each subject was asked to modify their gait in order to vary the magnitude of their MTFF. All subjects were able to increase their MTFF, whereas only 3 subjects could decrease it, and only after receiving verbal suggestions about possible gait modification strategies. Results indicate the important role of knee muscle activation patterns in modulating the MTFF. While this study focused on the knee, the technology can be extended to examine the musculoskeletal tissue loads at different sites of the human body
Biofeedback for gait retraining based on real-time estimation of tibiofemoral joint contact forces
Biofeedback assisted rehabilitation and intervention technologies have the potential to modify clinically relevant biomechanics. Gait retraining has been used to reduce the knee adduction moment, a surrogate of medial tibiofemoral joint loading often used in knee osteoarthritis research. In this study we present an electromyogram-driven neuromusculoskeletal model of the lower-limb to estimate, in real-time, the tibiofemoral joint loads. The model included 34 musculotendon units spanning the hip, knee, and ankle joints. Full-body inverse kinematics, inverse dynamics, and musculotendon kinematics were solved in real-time from motion capture and force plate data to estimate the knee medial tibiofemoral contact force (MTFF). We analyzed 5 healthy subjects while they were walking on an instrumented treadmill with visual biofeedback of their MTFF. Each subject was asked to modify their gait in order to vary the magnitude of their MTFF. All subjects were able to increase their MTFF, whereas only 3 subjects could decrease it, and only after receiving verbal suggestions about possible gait modification strategies. Results indicate the important role of knee muscle activation patterns in modulating the MTFF. While this study focused on the knee, the technology can be extended to examine the musculoskeletal tissue loads at different sites of the human body
Universal quantum interfaces
To observe or control a quantum system, one must interact with it via an
interface. This letter exhibits simple universal quantum interfaces--quantum
input/output ports consisting of a single two-state system or quantum bit that
interacts with the system to be observed or controlled. It is shown that under
very general conditions the ability to observe and control the quantum bit on
its own implies the ability to observe and control the system itself. The
interface can also be used as a quantum communication channel, and multiple
quantum systems can be connected by interfaces to become an efficient universal
quantum computer. Experimental realizations are proposed, and implications for
controllability, observability, and quantum information processing are
explored.Comment: 4 pages, 3 figures, RevTe
NMR quantum computation with indirectly coupled gates
An NMR realization of a two-qubit quantum gate which processes quantum
information indirectly via couplings to a spectator qubit is presented in the
context of the Deutsch-Jozsa algorithm. This enables a successful comprehensive
NMR implementation of the Deutsch-Jozsa algorithm for functions with three
argument bits and demonstrates a technique essential for multi-qubit quantum
computation.Comment: 9 pages, 2 figures. 10 additional figures illustrating output spectr
Implementation of a Deutsch-like quantum algorithm utilizing entanglement at the two-qubit level, on an NMR quantum information processor
We describe the experimental implementation of a recently proposed quantum
algorithm involving quantum entanglement at the level of two qubits using NMR.
The algorithm solves a generalisation of the Deutsch problem and distinguishes
between even and odd functions using fewer function calls than is possible
classically. The manipulation of entangled states of the two qubits is
essential here, unlike the Deutsch-Jozsa algorithm and the Grover's search
algorithm for two bits.Comment: 4 pages, two eps figure
Solid-State Nuclear Spin Quantum Computer Based on Magnetic Resonance Force Microscopy
We propose a nuclear spin quantum computer based on magnetic resonance force
microscopy (MRFM). It is shown that an MRFM single-electron spin measurement
provides three essential requirements for quantum computation in solids: (a)
preparation of the ground state, (b) one- and two- qubit quantum logic gates,
and (c) a measurement of the final state. The proposed quantum computer can
operate at temperatures up to 1K.Comment: 16 pages, 5 figure
Fast Quantum Search Algorithms in Protein Sequence Comparison - Quantum Biocomputing
Quantum search algorithms are considered in the context of protein sequence
comparison in biocomputing. Given a sample protein sequence of length m (i.e m
residues), the problem considered is to find an optimal match in a large
database containing N residues. Initially, Grover's quantum search algorithm is
applied to a simple illustrative case - namely where the database forms a
complete set of states over the 2^m basis states of a m qubit register, and
thus is known to contain the exact sequence of interest. This example
demonstrates explicitly the typical O(sqrt{N}) speedup on the classical O(N)
requirements. An algorithm is then presented for the (more realistic) case
where the database may contain repeat sequences, and may not necessarily
contain an exact match to the sample sequence. In terms of minimizing the
Hamming distance between the sample sequence and the database subsequences the
algorithm finds an optimal alignment, in O(sqrt{N}) steps, by employing an
extension of Grover's algorithm, due to Boyer, Brassard, Hoyer and Tapp for the
case when the number of matches is not a priori known.Comment: LaTeX, 5 page
Testing integrability with a single bit of quantum information
We show that deterministic quantum computing with a single bit (DQC1) can
determine whether the classical limit of a quantum system is chaotic or
integrable using O(N) physical resources, where is the dimension of the
Hilbert space of the system under study. This is a square root improvement over
all known classical procedures. Our study relies strictly on the random matrix
conjecture. We also present numerical results for the nonlinear kicked top.Comment: Minor changes taking into account Howard Wiseman's comment:
quant-ph/0305153. Accepted for publication in Phys. Rev.
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