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Purpose Passive elevation of body temperature can induce an acute inflammatory response that has been proposed to be beneficial; however, it can be perceived as uncomfortable. Here, we investigate whether local cooling of the upper body during hot water immersion can improve perception without inhibiting the interleukin-6 (IL-6) response. Methods Nine healthy male participants (age: 22 ± 1 years, body mass: 83.4 ± 9.4 kg) were immersed up to the waist for three 60-min water immersion conditions: 42 °C hot water immersion (HWI), 42 °C HWI with simultaneous upper-body cooling using a fan (FAN), and 36 °C thermoneutral water immersion (CON). Blood samples to determine IL-6 plasma concentration were collected pre- and post-water immersion; basic affect and thermal comfort were assessed throughout the intervention. Results Plasma IL-6 concentration was higher for HWI and FAN when compared with CON (P P = 0.22; pre to post, HWI: 1.0 ± 0.6 to 1.5 ± 0.7 pg·ml−1, FAN: 0.7 ± 0.5 to 1.1 ± 0.5 pg·ml−1, CON: 0.5 ± 0.2 to 0.5 ± 0.2 pg·ml−1). At the end of immersion, basic affect was lowest for HWI (HWI: − 1.8 ± 2.0, FAN: 0.2 ± 1.6, CON 1.0 ± 2.1, P P Conclusion Local cooling of the upper body during hot water immersion improves basic affect and thermal comfort without inhibiting the acute IL-6 response.

In clinical rehabilitation, biofeedback increases patient’s motivation making it one of the most effective motor rehabilitation mechanisms. In this field, it is very helpful for the patient and even for the therapist to know the level of success and performance of the training process. New rehabilitation technologies allow new forms of therapy for patients with Range of Motion (ROM) disorders. The aim of this work is to introduce a simple biofeedback system in a clinical environment for ROM measurements, since there is currently a lack of practical and cost-efficient methods available for this purpose. The Microsoft Kinect™ introduces the possibility of low cost, non intrusive human motion analysis in the rehabilitation field. In this paper we conduct a comparison study of the accuracy in the computation of ROM measurements between the Kinect™ Skeleton Tracking provided by Microsoft and the proposed algorithm based on depth analysis. Experimental results showed that our algorithm is able to overcome the limitations of the Microsoft algorithm when the pose estimation is used as a measuring system making it a valuable rehabilitation tool.

Predicting human upper body motion involves resolving a high level of redundancy. It is preferable to resolve all possible inverse kinematic poses to a single human like pose. In this paper the relative benefits and difficulties in developing parameter based and optimized numerical models for predicting upper body posture are examined. The predicted poses of a joint limit constraint and an optimized relative rate constraint were calculated, both using the weighted least norm method. Results were then compared to the recorded motion of 10 healthy adult subjects. Both methods produced similar results, with an average RMS error of 8.9° and 8.2° for the joint limit and optimized methods respectively. Combination of methods produced a marginal increase in performance with an average RMS error of 7.6°.

A special jacket actuated by Mckibben pneumatic artificial muscles is developed, which is called as “jacket robot”. It can be put on the human upper body and the two arms to help them act. To satisfy the requirement for perceiving the arm actions automatically, an action intention recognition technology based on the acceleration signal is investigated. The paper introduces the constitution of the jacket robot, its main functions and its main technical specification. The designation idea about the recognition method is emphasized. The related experiment shows that the method is efficient.

A walking motion of a humanoid has been analyzed or developed without considering motions of the remaining parts of the humanoid. In order to perform tasks in the human’s living environment, a walking motion and assigned tasks must be considered at the same time. In this paper, a whole body motion generation method, i.e., the motion embedded CoM Jacobian method is introduced. With the method, a balance control and assigned motions are separated and thus, the assigned motions can be generated without considering balance of a humanoid. As experimental examples, whole body motion of a humanoid is assigned by the tele-operation. Arbitrarily assigned upper body motions and independently generated walking motions are combined to generate a balanced whole body motion with the suggested methods.

Therapists and researchers have studied the importance of virtual reality (VR) environments in physical therapy interventions for people with different conditions such as stroke, Parkinson’s disease, and cerebral palsy. Most of these VR systems do not integrate clinical assessment of outcome measures as an automated objective of the system. Moreover, these systems do not allow real-time adjustment of the system characteristics that is necessary to individualize the intervention. We discuss a new VR game designed to improve upper-arm motor function through repetitive arm exercises. An automated method is used to extract outcome measures of upper extremity movements using the Fugl-Meyer assessment methodology. The accuracy of the system was validated based on trials with eighteen adult subjects. With a corresponding average assessment error of less than 5%, the developed system shows to be a promising tool for therapists to use in individualizing the intervention for individuals with upper-body motor impairments.

This paper focuses on a facilitated and intuitive representation of upper-body gestures for developers. The representation is based on the user motion parameters, particularly the rotational and translational components of body segments during a gesture. The developed static representation aims to provide a rapid visualization of the complexity for each body segment involved in the gesture for static representations. The model and algorithms used to produce the representation have been applied to a dataset of 10 representative gestures to illustrate the model.

In this paper, we describe an algorithm and an interactive content using the idea to experience feeling of bird’s flying by using gesture recognition of a user’s upper body. In the algorithm we assume that gesture is composed of several key poses. So, in order to recognize the user’s gesture, we firstly classify the user pose into the several predefined key poses and then analyze the sequence of the poses. In the key pose recognition procedure, the information of upper-body configuration is estimated by using joint locations of depth image from a Kinect camera. If the user performs a consecutive motion, the content recognizes the key poses and then synthesizes a gesture according to the order of the key poses. The stage of the content is consisted with three parts in order to enjoy the various flight experiences.

The present study aimed at investigating how emotion affect the kinematic aspect of human walking. The gaits of eight professional actors expressing different types of emotions (neutral, joy, anger, sadness and fear) during walking were recorded and analyzed in the sagittal plane. We show both step-related behavioural changes (in terms of step length, speed,etc.) that are common to different emotions and emotion-specific body configuration changes (mainly at the level of the upper body posture) during emotional gaits. Since the overall speed of walking is another major variant in walking, natural walking at different speeds were recorded in another session for a control.

We propose a method for accurately localizing anatomical landmarks in 3D medical volumes based on dense matching of parts-based graphical models. Our novel approach replaces population mean models by jointly leveraging weighted combinations of labeled exemplars (both spatial and appearance) to obtain personalized models for the localization of arbitrary landmarks in upper body images. We compare the method to a baseline population-mean graphical model and atlas-based deformable registration optimized for CT-CT registration, by measuring the localization accuracy of 22 anatomical landmarks in clinical 3D CT volumes, using a database of 83 lung cancer patients. The average mean localization error across all landmarks is 2.35 voxels. Our proposed method outperforms deformable registration by 73%, 93% for the most improved landmark. Compared to the baseline population-mean graphical model, the average improvement of localization accuracy is 32%; 67% for the most improved landmark.

While studying body postures in relation to mood is not a new concept, the majority of these studies rely on actors interpretations. This project investigated the temporal aspects of naturalistic body postures while users listened to mood inducing music. Video data was collected while participants listened to eight minutes of music during two sessions (happy and sad) in a within-subjects design. Subjectively reported mood scores validated that mood did differ significantly for valence and energy. Video analysis consisted of postural ratings for the head, shoulders, trunk, arms, and head and hand tapping. Results showed significant differences for the majority of these dimensions by mood. This study showed that certain body postures are indicative of certain mood states in a naturalistic setting.

Occupational therapists use rehabilitation training to attempt to recover use of the fingers in people whose fingers have been paralyzed by brain damage or some other means. Our research aims to support some of this training using computer technology, and we are developing a rehabilitation system that is both small and portable. This paper will describe the finger training system that we have developed.

In this paper, a systematic comparative analysis of laserbased tracking methods, at feet and upper-body height, is performed. To this end, we created a well defined dataset, including challenging but realistic person movement trajectories, appearing in public operational environments, recorded with multiple laser range finders. In order to evaluate and compare the tracking results, we applied and adapted a performance metric, known from the Computer Vision area. The dataset in combination with this performance metric enables us to perform systematic and repeatable experiments for benchmarking laser-based person trackers.

Resurfacing of the face and neck in burn survivors is best accomplished using skin from the “blush areas” of the upper body including the neck, shoulders, and upper chest. This gives the best color and texture match to the remaining normal skin of the face and neck.

We are studying how Embodied Conversational Agents (ECAs) express communication behavior with cultural background. The objective of this study is the proposition of the modified Capture and Express Behavior Environment (CEBE) in which a person can interact with ECAs controlled by the captured behavior of another person with cultural background. In this paper, we discuss modifications and concepts of CEBE to apply CEBE for investigations to realize an ECA with cultural background. The prototype system could capture basic human behavior, such as head direction, posture of the upper body, and 3D angles of arms, when each part of the body, such as head, hands, arms and trunk. In addition, the system could control a robot or a virtual agent based on the detected data. We have to develop some implementations to interact with people with cultural background.

This paper investigates the efficiency of the real-time embedded system in our humanoid robot, Betty. In this paper we only discuss the upper body of Betty. Based on several experiments of different queue data structures, communication protocols and PID controller implementations, we measured and analysed the latencies and jitters of Betty’s responses. The experimental results indicate the best configuration to optimise the performance of Betty’s Control Program.

Compact spatio temporal representation of human gait in form of gait enery image (GEI) has attracted lot of attention in recent years for biometric gait recognition. Researchers have reported very high recognition rates for normal walk sequences. However, the rates come down when the subjects are wearing a jacket or coat, or are carrying a bag. This paper shows that the performance for the variant situations can be improved upon considerably by constructing the GEI with sway alignment instead of upper body alignment, and selecting just the required number of rows from the bottom of the silhouette as inputs for an unsupervised feature selection approach. The improvement in recognition rates are established by comparing performances with existing results on a large gait database.

In this paper, we will present the main problems encountered for reconstructing in-vehicle reach postures. Among the 2176 successfully captured movements, about 7.4% of them were considered as "bad quality" with a high residual error between reconstructed and measured marker positions. They mainly correspond to the far targets and in the direction that one has to elevate the arm. The results of the present study strongly suggest that a more realistic kinematic model of the upper body including the shoulder complex, pelvis and spine is required. In addition, the natural coordination between joint axes should also be used for compensating the lack of information in case of under-constraint situation and for correcting the uncertainty of surface markers positions.

This paper proposes a marker-less motion measurement and analysis system for quantitative evaluation of movements of infants. In this system, movements of infants are measured using a single video camera, and then changes of body position and motion in infants are calculated from binarized images, which are extracted using background subtraction or inter-frame difference. Furthermore, eight indices are derived for quantitative evaluation of movements of infants, such as body activity level and amount of body motion. Base on these data, doctors can therefore get an intuitive understanding of the movements of infants without long-period observation. This is considered helpful for supporting diagnosis and detecting of infants’ disability or function diseases in the early stages. In this paper, the evaluation indices and features of movement between 14 full-term infants (FTIs) and 11 low-birthweight infants (LBWIs) are compared using the prototype developed. The experimental results show that, with some LBWIs, the upper body moves more than the lower body compared with FTIs, demonstrating that the proposed system can quantitatively evaluate the difference between the movements of FTIs and LBWIs.

This paper presents a visual tracking algorithm that is based on CamShift. Both the face and upper body are utilized simultaneously to perform tracking. They are first tracked independently by applying two separate CamShifts which continue tracking from the locations determined in the last time step and use only color probability images. Next, the candidate locations are subjected to CamShift which operates on distributions reflecting additionally geometrical relations between the face and the body. The aim of the CamShift-based searching in the joint color-spatial space is to find the mode. Experimental tracking results on meeting video recordings are presented. They demonstrate that this algorithm is superior over traditional CamShift. Furthermore, it is very simple and computationally fast.

Figure 128 sketches how the femur is loaded when standing on one leg. The abductor muscles play an important role here, preventing the upper body supported on the ball of the hip joint from tipping inwards (Fig. 128A). Because of the unfavourable lever relationships, the neck of the femur must transmit about 2.5 to 6 times body weight as axial loading (Fig. 128B). These enormous loads can only be coped with by an outstandingly well-adapted design. In the zone near the joint the femur is filled with trabecular bone, also called spongiform bone. This is a micro-framework of very fine small struts of bone which fill the whole head and neck of the femur. Further down they run into the bone-free marrow cavity in the middle, and laterally into the compact bone wall (cortical bone). In the lower region, the femur, which is almost exclusively loaded in bending, is a simple tube with a non-circular cross-section. This is certainly sensible, for we have the highest bending stresses at the edge, and in the middle, i.e. in the marrow cavity where there is no bone, the stresses are correspondingly equal to zero. (A hollow tree is therefore not so bad, for it too has no bending loads in the middle!)

In computed tomography (CT) systems with a continuately rotating tube and detector system, spiral CT has become available as a supportive method to fast dynamic CT [5, 6, 9]. Spiral CT enables us to scan a volume of 23 cm in length in a time of 24 s. Thus, the whole upper body may be scanned in a single breath hold. The method seems suitable to examine the early, mostly arterial perfusion phase of the entire liver in a single scan. In addition, the method might reduce breathing artifacts. The aim of this study was to examine which additional possibilities spiral CT offers compared with dynamic CT for the examination of the liver.