Dataset Information

Haptic exploratory behavior during object discrimination: a novel automatic annotation method.

ABSTRACT: In order to acquire information concerning the geometry and material of handheld objects, people tend to execute stereotypical hand movement patterns called haptic Exploratory Procedures (EPs). Manual annotation of haptic exploration trials with these EPs is a laborious task that is affected by subjectivity, attentional lapses, and viewing angle limitations. In this paper we propose an automatic EP annotation method based on position and orientation data from motion tracking sensors placed on both hands and inside a stimulus. A set of kinematic variables is computed from these data and compared to sets of predefined criteria for each of four EPs. Whenever all criteria for a specific EP are met, it is assumed that that particular hand movement pattern was performed. This method is applied to data from an experiment where blindfolded participants haptically discriminated between objects differing in hardness, roughness, volume, and weight. In order to validate the method, its output is compared to manual annotation based on video recordings of the same trials. Although mean pairwise agreement is less between human-automatic pairs than between human-human pairs (55.7% vs 74.5%), the proposed method performs much better than random annotation (2.4%). Furthermore, each EP is linked to a specific object property for which it is optimal (e.g., Lateral Motion for roughness). We found that the percentage of trials where the expected EP was found does not differ between manual and automatic annotation. For now, this method cannot yet completely replace a manual annotation procedure. However, it could be used as a starting point that can be supplemented by manual annotation.

SUBMITTER: Jansen SE

PROVIDER: S-EPMC4319767 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Haptic exploratory behavior during object discrimination: a novel automatic annotation method.

Jansen Sander E M SE Bergmann Tiest Wouter M WM Kappers Astrid M L AM

PloS one 20150206 2

In order to acquire information concerning the geometry and material of handheld objects, people tend to execute stereotypical hand movement patterns called haptic Exploratory Procedures (EPs). Manual annotation of haptic exploration trials with these EPs is a laborious task that is affected by subjectivity, attentional lapses, and viewing angle limitations. In this paper we propose an automatic EP annotation method based on position and orientation data from motion tracking sensors placed on bo ...[more]

PMID: 25658703

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Project description:Tail biting is a serious welfare concern in pig production. It not only causes distress for victims, but may occur where pigs are unable to cope, and become biters. An animal's ability to cope with stressful situations may vary between individuals, but the behavioral response could be consistent across different fear eliciting situations. We exposed 75 pigs to open field (OF) and novel object (NO) tests at 14 weeks of age. Within each pen of pigs (n = 16 pens, 55 pigs/pen), 6 pigs were selected for testing using the following criteria: 3 pigs that had severe bite wounds (BITTEN), 1 confirmed biter (BITER), 1 pig which could be easily approached and trained to provide a saliva sample (BOLD) and 1 pig which was extremely evasive, and was unable to be trained to willingly provide a saliva sample (SHY). Given that responses may be consistent in different scenarios, we hypothesized that SHY pigs would display more characteristics of a fear response (i.e., less movement in the open field, more time spent by the door, and longer latency to approach the novel object) than human BOLD pigs. We also hypothesized that BITTEN pigs would behave similarly to SHY and BITERS similarly to BOLD. The BOLD and BITER pigs spent more time exploring (P < 0.05) and less time by the door (P < 0.01) than the BITTEN and SHY pigs. Although there was an overall increase in cortisol level from before to after the tests (P < 0.001), this was only significant for BITTEN (P < 0.001) and SHY (P < 0.05) pigs. Therefore, as hypothesized, for several measures, BOLD, and BITER pigs behaved similarly, and differently to SHY and BITTEN. However, the low sample size potentially meant that for several measures, although numeric differences were in the direction hypothesized, there were no statistical differences. Further work in which a greater number of BITER pigs were included in the sample, may elucidate our hypotheses more clearly, as to whether responses to fear tests in pigs could be associated with the likelihood of being a tail biter, or victim.

Project description:BackgroundTumor proliferation speed, most commonly assessed by counting of mitotic figures in histological slide preparations, is an important biomarker for breast cancer. Although mitosis counting is routinely performed by pathologists, it is a tedious and subjective task with poor reproducibility, particularly among non-experts. Inter- and intraobserver reproducibility of mitosis counting can be improved when a strict protocol is defined and followed. Previous studies have examined only the agreement in terms of the mitotic count or the mitotic activity score. Studies of the observer agreement at the level of individual objects, which can provide more insight into the procedure, have not been performed thus far.MethodsThe development of automatic mitosis detection methods has received large interest in recent years. Automatic image analysis is viewed as a solution for the problem of subjectivity of mitosis counting by pathologists. In this paper we describe the results from an interobserver agreement study between three human observers and an automatic method, and make two unique contributions. For the first time, we present an analysis of the object-level interobserver agreement on mitosis counting. Furthermore, we train an automatic mitosis detection method that is robust with respect to staining appearance variability and compare it with the performance of expert observers on an "external" dataset, i.e. on histopathology images that originate from pathology labs other than the pathology lab that provided the training data for the automatic method.ResultsThe object-level interobserver study revealed that pathologists often do not agree on individual objects, even if this is not reflected in the mitotic count. The disagreement is larger for objects from smaller size, which suggests that adding a size constraint in the mitosis counting protocol can improve reproducibility. The automatic mitosis detection method can perform mitosis counting in an unbiased way, with substantial agreement with human experts.

Dataset Information

Haptic exploratory behavior during object discrimination: a novel automatic annotation method.

Publications

Haptic exploratory behavior during object discrimination: a novel automatic annotation method.

Similar Datasets

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