BACKGROUND: Physiological motion of the lumbar spine is a topic of interest for musculoskeletal health care professionals since abnormal motion is believed to be related to lumbar complaints. Many researchers have described ranges of motion for the lumbar spine, but only few have mentioned specific motion patterns of each individual segment during flexion and extension, mostly comprising the sequence of segmental initiation in sagittal rotation. However, an adequate definition of physiological motion is still lacking. For the lower cervical spine, a consistent pattern of segmental contributions in a flexion-extension movement in young healthy individuals was described, resulting in a definition of physiological motion of the cervical spine.
OBJECTIVE: This study aimed to define the lumbar spines\' physiological motion pattern by determining the sequence of segmental contribution in sagittal rotation of each vertebra during maximum flexion and extension in healthy male participants.
METHODS: Cinematographic recordings were performed twice in 11 healthy male participants, aged 18-25 years, without a history of spine problems, with a 2-week interval (time point T1 and T2). Image recognition software was used to identify specific patterns in the sequence of segmental contributions per individual by plotting segmental rotation of each individual segment against the cumulative rotation of segments L1 to S1. Intraindividual variability was determined by testing T1 against T2. Intraclass correlation coefficients were tested by reevaluation of 30 intervertebral sequences by a second researcher.
RESULTS: No consistent pattern was found when studying the graphs of the cinematographic recordings during flexion. A much more consistent pattern was found during extension, especially in the last phase. It consisted of a peak in rotation in L3L4, followed by a peak in L2L3, and finally, in L1L2. This pattern was present in 71% (15/21) of all recordings; 64% (7/11) of the participants had a consistent pattern at both time points. Sequence of segmental contribution was less consistent in the lumbar spine than the cervical spine, possibly caused by differences in facet orientation, intervertebral discs, overprojection of the pelvis, and muscle recruitment.
CONCLUSIONS: In 64% (7/11) of the recordings, a consistent motion pattern was found in the upper lumbar spine during the last phase of extension in asymptomatic young male participants. Physiological motion of the lumbar spine is a broad concept, influenced by multiple factors, which cannot be captured in a firm definition yet.
BACKGROUND: ClinicalTrials.gov NCT03737227; https://clinicaltrials.gov/ct2/show/NCT03737227.
UNASSIGNED: RR2-10.2196/14741.

BACKGROUND: Knowledge of protein motions is significant to understand its functions. While currently available databases for protein motions are mostly focused on overall domain motions, little attention is paid on local residue motions. Albeit with relatively small scale, the local residue motions, especially those residues in binding pockets, may play crucial roles in protein functioning and ligands binding.
RESULTS: A comprehensive protein motion database, namely D3PM, was constructed in this study to facilitate the analysis of protein motions. The protein motions in the D3PM range from overall structural changes of macromolecule to local flip motions of binding pocket residues. Currently, the D3PM has collected 7679 proteins with overall motions and 3513 proteins with pocket residue motions. The motion patterns are classified into 4 types of overall structural changes and 5 types of pocket residue motions. Impressively, we found that less than 15% of protein pairs have obvious overall conformational adaptations induced by ligand binding, while more than 50% of protein pairs have significant structural changes in ligand binding sites, indicating that ligand-induced conformational changes are drastic and mainly confined around ligand binding sites. Based on the residue preference in binding pocket, we classified amino acids into \"pocketphilic\" and \"pocketphobic\" residues, which should be helpful for pocket prediction and drug design.
CONCLUSIONS: D3PM is a comprehensive database about protein motions ranging from residue to domain, which should be useful for exploring diverse protein motions and for understanding protein function and drug design. The D3PM is available on www.d3pharma.com/D3PM/index.php .

Human Activity Recognition (HAR) systems are designed to read sensor data and analyse it to classify any detected movement and respond accordingly. However, there is a need for more responsive and near real-time systems to distinguish between false and true alarms. To accurately determine alarm triggers, the motion pattern of legitimate users need to be stored over a certain period and used to train the system to recognise features associated with their movements. This training process is followed by a testing cycle that uses actual data of different patterns of activity that are either similar or different to the training data set. This paper evaluates the use of a combined Convolutional Neural Network (CNN) and Naive Bayes for accuracy and robustness to correctly identify true alarm triggers in the form of a buzzer sound for example. It shows that pattern recognition can be achieved using either of the two approaches, even when a partial motion pattern is derived as a subset out of a full-motion path.

This paper presents a new approach for estimating the motion state of a target that is maneuvered by an unknown human from observations. To improve the estimation accuracy, the proposed approach associates the recurring motion behaviors with human intentions, and models the association as an intention-pattern model. The human intentions relate to labels of continuous states; the motion patterns characterize the change of continuous states. In the preprocessing, an Interacting Multiple Model (IMM) estimation technique is used to infer the intentions and extract motions, which eventually construct the intention-pattern model. Once the intention-pattern model has been constructed, the proposed approach incorporate the intention-pattern model to estimation using any state estimator including Kalman filter. The proposed approach not only estimates the mean using the human intention more accurately but also updates the covariance using the human intention more precisely. The performance of the proposed approach was investigated through the estimation of a human-maneuvered multirotor. The result of the application has first indicated the effectiveness of the proposed approach for constructing the intention-pattern model. The ability of the proposed approach in state estimation over the conventional technique without intention incorporation has then been demonstrated.

The existing computational models used to estimate motion sickness are incapable of describing the fact that the predictability of motion patterns affects motion sickness. Therefore, the present study proposes a computational model to describe the effect of the predictability of dynamics or the pattern of motion stimuli on motion sickness. In the proposed model, a submodel - in which a recursive Gaussian process regression is used to represent human features of online learning and future prediction of motion dynamics - is combined with a conventional model of motion sickness based on an observer theory. A simulation experiment was conducted in which the proposed model predicted motion sickness caused by a 900 s horizontal movement. The movement was composed of a 9 m repetitive back-and-forth movement pattern with a pause. Regarding the motion condition, the direction and timing of the motion were varied as follows: (a) Predictable motion (M_P): the direction of the motion and duration of the pause were set to 8 s; (b) Motion with unpredicted direction (M_dU): the pause duration was fixed as in (M_P), but the motion direction was randomly determined; (c) Motion with unpredicted timing (M_tU): the motion direction was fixed as in (M_P), but the pause duration was randomly selected from 4 to 12 s. The results obtained using the proposed model demonstrated that the predicted motion sickness incidence for (M_P) was smaller than those for (M_dU) and (M_tU) and no considerable difference was found between M_dU and M_tU. This tendency agrees with the sickness patterns observed in a previous experimental study in which the human participants were subject to motion conditions similar to those used in our simulations. Moreover, no significant differences were found in the predicted motion sickness incidences at different conditions when the conventional model was used.

Purpose: Prosthetic heart valve designs must be rigorously tested using cardiovascular equipment. The valve orifice area over time constitutes a key quality metric which is typically assessed manually, thus a tedious and error-prone task. From a computer vision viewpoint, a major unsolved issue lies in the orifice being partly occluded by the leaflets\' inner side or inaccurately depicted due to its transparency. Here, we address this issue, which allows us to focus on the accurate and automatic computation of valve orifice areas. Approach: We propose a segmentation approach based on the detection of the leaflets\' free edges. Using video frames recorded with a high-speed digital camera during in vitro simulations, an initial estimation of the orifice area is first obtained via active contouring and thresholding and then refined to capture the leaflet free edges via a curve transformation mechanism. Results: Experiments on video data from pulsatile flow testing demonstrate the effectiveness of our approach: a root-mean-square error (RMSE) on the temporal extracted orifice areas between 0.8% and 1.2%, an average Jaccard similarity coefficient between 0.933 and 0.956, and an average Hausdorff distance between 7.2 and 11.9 pixels. Conclusions: Our approach significantly outperformed a state-of-the-art algorithm in terms of evaluation metrics related to valve design (RMSE) and computer vision (accuracy of the orifice shape). It can also cope with lower quality videos and is better at processing frames showing an almost closed valve, a crucial quality for assessing valve design malfunctions related to their improper closing.

BACKGROUND: Breast cancer (BC) is the most common cancer among women in developed countries. Several types of surgical interventions are commonly used in BC, such as mastectomy and quadrantectomy, followed by radiation or not. Today, BC rehabilitation can help survivors obtain and maintain the highest physical, social, psychological, and vocational functioning possible, within the limits that are created by cancer and its treatments.
OBJECTIVE: To verify, before and after a specific rehabilitation protocol treatment, the recovery of the fluidity of the reaching movement.
METHODS: Patients after BC surgery were enrolled and assigned by cluster randomization into 2 groups through a block randomization list: mastectomy (Mas) and quadrantectomy (Quad). Evaluation scales (DASH and VAS) were administered, and biomechanical evaluations were performed for each group before treatment (T0 = baseline), at the end of the rehabilitative treatment (T1 = 12 sessions, 2/week), and after 3 months of follow-up (T2).
RESULTS: Fifty-nine (Mas group = 29; Quad group = 30) after BC surgery were enrolled. VAS scores improved along the evaluation times at T0-T1 and T0-T2 (p < 0.001), without a statistically significant difference between groups. With regard to the normalized jerk, there was no significant interaction between time group (F = 2.029; p = 0.136). There was a significant decrease between T0-T1 and T1-T2 (F = 60.189; p < 0.001). Velocity improved significantly between T0-T1 and T1-T2 (F = 10.322; p < 0.001). There was a significant interaction for the elbow angle at the end of movement between time and group at T2 (F = 5.022; p = 0.029).
CONCLUSIONS: The integrated, low-intensity, rehabilitative intervention is effective, even if it is not performed in the first period after BC surgery, without any difference between mastectomy and quadrantectomy.

We investigated how differential payoffs affect the temporal discrimination of humans. In a temporal bisection task, participants learned to make one response after a short sample and another after a long sample. When presented with a range of intermediate samples, the proportion of responses fitted well a Gaussian-like distribution function characterized by a location (bias), a scale (sensitivity) parameter, and two asymptote (discrimination) parameters. In Experiment 1, when one response yielded more reinforcers than the other, parameters were unaltered, but overall responses increased for the response producing higher payoffs. In Experiment 2, we used a video game to track motion during the sample and participants learned to approach the \"short\" response location at sample onset and remain there before departing to the \"long\" location on long trials. Departure times were shorter when \"long\" choices produced higher payoffs than \"short\" and matched well the shifted psychometric functions. However, on some trials, subjects were biased for short, returning to the short side after having departed towards long. Evidence was found for effects of differential payoffs on response bias, but discrimination and sensitivity did not change consistently. These results favor a behavioral account of timing processes.

BACKGROUND: Physiological motion of the lumbar spine is a subject of interest for musculoskeletal health care professionals, as abnormal motion is believed to be related to lumbar conditions and complaints. Many researchers have described ranges of motion for the lumbar spine, but only a few have mentioned specific motion patterns of each individual segment during flexion and extension. These motion patterns mostly comprise the sequence of segmental initiation in sagittal rotation. However, an adequate definition of physiological motion of the lumbar spine is still lacking. The reason for this is the reporting of different ranges of motion and sequences of segmental initiation in previous studies. Furthermore, due to insufficient fields of view, none of these papers have reported on maximum flexion and extension motion patterns of L1 to S1. In the lower cervical spine, a consistent pattern of segmental contributions was recently described. In order to understand physiological motion of the lumbar spine, it is necessary to systematically study motion patterns, including the sequence of segmental contribution, of vertebrae L1 to S1 in healthy individuals during maximum flexion and extension.
OBJECTIVE: This study aims to define the lumbar spines\' physiological motion pattern of vertebrae L1, L2, L3, L4, L5, and S1 by determining the sequence of segmental contribution and the sequence of segmental initiation of motion in sagittal rotation of each vertebra during maximum flexion and extension. The secondary endpoint will be exploring the possibility of analyzing the intervertebral horizontal and vertical translation of each vertebra during maximum flexion and extension.
METHODS: Cinematographic recordings will be performed in 11 healthy male participants, aged 18-25 years, without a history of spine problems. Cinematographic flexion and extension recordings will be made at two time points with a minimum 2-week interval in between.
RESULTS: The study has been approved by the local institutional medical ethical committee (Medical Research Ethics Committee of Zuyderland and Zuyd University of applied sciences) on September 24, 2018. Inclusion of participants will be completed in 2020.
CONCLUSIONS: If successful, these physiological motion patterns can be compared with motion patterns of patients with lumbar conditions before or after surgery. Ultimately, researchers may be able to determine differences in biomechanics that can potentially be linked to physical complaints like low back pain.
BACKGROUND: ClinicalTrials.gov NCT03737227; https://clinicaltrials.gov/ct2/show/NCT03737227.
UNASSIGNED: DERR1-10.2196/14741.

Literature is still limited regarding reports of non-invasive assessment of the cervical range of motion in normal subjects. Investigations into compensatory motions, defined as the contribution of an additional direction to the required motion, are also limited.The objectives of this work were to develop and assess a reliable method for measuring the cervical range of motion in order to investigate motion and compensatory strategies.
Ninety-seven no neck-related pain subjects (no severe cervical pathology, 57 women, age: 28.3 ± 7.5y. old, BMI: 22.5 ± 3.2 kg/m2) underwent a non-invasive cervical range of motion assessment protocol. In-vivo head\'s motion relative to the thorax was assessed through the measurement of the main angular amplitudes in the 3 directions (flexion/extension, axial rotations and lateral inclinations) and associated compensatory motions using an opto-electronic acquisition system.
The principal motion reproducibility resulted in intra-class correlation coefficients ranging from 0.81 to 0.86. The following maximum ranges of motion were found: 127.4 ± 15.1° of flexion/extension, 89.3 ± 12° of lateral inclinations and 146.4 ± 13° of axial rotations after 6 outlier exclusions. Compensatory motions highly depend on the associated principal motion: for flexion/extension: (3.5 ± 7.6;-2.1 ± 7.8°), for rotation: (25.7 ± 17.9°;0.4 ± 4.7)°, for inclination: (22.9 ± 34.7°;-0.04 ± 8.7°). Age, BMI and weight significantly correlated with flexions (p < 0.032). Motion patterns were identified through clustering.
This kinematic analysis has been proven to be a reliable diagnostic tool for the cervical range of motion. The non-unicity and variability of motion patterns through the clustering of motion strategy identification have been shown. Compensatory motions contributed to such motion pattern definition despite presenting significant intra-individual variability.