Cardiovascular responses of older adults to downhill (DTW, –10% incline) and level treadmill walking (0%) at self-selected walking speed (SSWS) were examined. Fifteen participants (age 68 ± 4 yr, height 1.69 ± 0.08 m, body mass 74.7 ± 8.1 kg) completed two 15-min walks at their SSWS (4.6 ± 0.6 km/hr). Cardiovascular responses were estimated using an arterial-volume finger clamp and infrared plethysmography. Oxygen consumption was 25% lower during DTW and associated with lower values for stroke volume (9.9 ml/beat), cardiac output (1.0 L/min), arteriovenous oxygen difference (a-v O2 diff, 2.4 ml/L), and systolic blood pressure (10 mmHg), with no differences in heart rate or diastolic and mean arterial blood pressure. Total peripheral resistance (TPR) was higher (2.11 mmHg) during DTW. During downhill walking, an exercise performed with reduced cardiac strain, endothelial changes, and reduced metabolic demand may be responsible for the different responses in TPR and a-v O2 diff. Future work is warranted on whether downhill walking is suitable for higher risk populations.
Mandy L. Gault, Richard E. Clements and Mark E.T. Willems
Andrew E. Littmann, Masaki Iguchi, Sangeetha Madhavan, Jamie L. Kolarik and Richard K. Shields
There is conflicting evidence in the literature regarding whether women with anterior cruciate ligament reconstruction (ACLR) demonstrate impaired proprioception. This study examined dynamic-position-sense accuracy and central-nervous-system (CNS) processing time between those with and without long-term ACLR.
To compare proprioception of knee movement in women with ACLR and healthy controls.
Human neuromuscular performance laboratory.
11 women (age 22.64 ± 2.4 y) with ACLR (1.6–5.8 y postsurgery) and 20 women without (age 24.05 ± 1.4 y).
The authors evaluated subjects using 3 methods to assess position sense. During knee flexion at pseudorandomly selected speeds (40°, 60°, 80°, 90°, and 100°/s), subjects indicated with their index finger when their knee reached a predetermined target angle (50°). Accuracy was calculated as an error score. CNS processing time was computed using the time to detect movement and the minimum time of angle indication. Passive and active joint-position sense were also determined at a slow velocity (3°/s) from various knee-joint starting angles.
Main Outcome Measurements:
Absolute and constant error of target angle, indication accuracy, CNS processing time, and perceived function.
Both subject groups showed similar levels of error during dynamic-position-sense testing, despite continued differences in perceived knee function. Estimated CNS processing time was 260 ms for both groups. Joint-position sense during slow active or passive movement did not differ between cohorts.
Control and ACLR subjects demonstrated similar dynamic, passive, and active joint-position-sense error and CNS processing speed even though ACLR subjects reported greater impairment of function. The impairment of proprioception is independent of post-ACLR perception of function.
Arend W. A. Van Gemmert and Hans-Leo Teulings
The term graphonomics refers to the scientific and technological effort involved in identifying relationships between the planning and generation of handwriting and drawing movements, the resulting spatial traces of writing and drawing instruments (either conventional or electronic), and the dynamic features of these traces (International Graphonomics Society, 1987). Since the term graphonomics was coined in 1982, the multidisciplinary nature of graphonomic research has attracted scientists in several fundamental and applied areas, including motor control, motor learning, motor development, movement disorders, neuropsychology, biophysics, forensic science, computer science, cognitive science, artificial intelligence, among others. The many different research areas that are represented at the biennial conferences of the International Graphonomic Society (IGS) are exemplified by the variety of research papers published in special issues and books resulting from these conferences (cf. Meulenbroek & Van Gemmert, 2003; Simner & Girouard, 2000; Van Galen & Morasso, 1998; Simner, Leedham, & Thomassen, 1996; Faure, Keuss, Lorette, & Vinter, 1994; Simner, Hulstijn, & Girouard, 1994; Plamondon, 1993; Van Galen & Stelmach, 1993; Van Galen, Thomassen, & Wing, 1991; Wann, Wing, & Søvik, 1991; Plamondon & Leedham, 1990; Plamondon, Suen, & Simner, 1989; Kao, Van Galen, & Hoosain, 1986; Thomassen, Keuss, Van Galen, & Grootveld, 1983). Starting at the 10th IGS conference in Nijmegen, 2001, the influence of multidisciplinary collaborations and technical advancements expanded the scope of paradigms of researchers interested in graphonomics (e.g., finger control, isometric force control, brain imaging). This expansion of paradigms and the multidisciplinary nature of graphonomic research was pushed further into the center of fine motor control at the 11th IGS conference held in Scottsdale, 2003. This special issue of Motor Control, containing papers from this conference, exemplifies this progress.
Adriana V. Savescu, Mark L. Latash and Vladimir M. Zatsiorsky
This article proposes a technique to calculate the coefficient of friction for the fingertip– object interface. Twelve subjects (6 males and 6 females) participated in two experiments. During the first experiment (the imposed displacement method), a 3-D force sensor was moved horizontally while the subjects applied a specified normal force (4 N, 8 N, 12 N) on the surface of a sensor covered with different materials (sandpaper, cotton, rayon, polyester, and silk).The normal force and the tangential force (i.e., the force due to the sensor motion) were recorded. The coefficient of friction (µd) was calculated as the ratio between the tangential force and the normal force. In the second experiment (the beginning slip method), a small instrumented object was gripped between the index finger and the thumb, held stationary in the air, and then allowed to drop. The weight (200 g, 500 g, and 1,000 g) and the surface (sandpaper, cotton, rayon, polyester, and silk) in contact with the digits varied across trials. The same sensor as in the first experiment was used to record the normal force (in a horizontal direction) and the tangential force (in the vertical direction). The slip force (i.e., the minimal normal force or grip force necessary to prevent slipping) was estimated as the force at the moment when the object just began to slip. The coefficient of friction was calculated as the ratio between the tangential force and the slip force. The results show that (1) the imposed displacement method is reliable; (2) except sandpaper, for all other materials the coefficient of friction did not depend on the normal force; (3) the skin–sandpaper coefficient of friction was the highest µd = 0.96 ± 0.09 (for 4-N normal force) and the skin–rayon rayon coefficient of friction was the smallest µd = 0.36 ± 0.10; (4) no significant difference between the coefficients of friction determined with the imposed displacement method and the beginning slip method was observed. We view the imposed displacement technique as having an advantage as compared with the beginning slip method, which is more cumbersome (e.g., dropped object should be protected from impacts) and prone to subjective errors owing to the uncertainty in determining the instance of the slip initiation (i.e., impeding sliding).
Inge Tuitert, Tim A. Valk, Egbert Otten, Laura Golenia and Raoul M. Bongers
The uncontrolled manifold (UCM) method is a well-established approach to assessing the coordination of multiple degrees of freedom (DoF) in synergies that stabilize performance in human actions. The method has been applied to a variety of actions, such as sit-to-stance, finger-force production, and
Alessia Longo and Ruud Meulenbroek
was approved by the local ethics committee, and all subjects signed informed consent forms prior to the experiment. Experimental Task Participants moved the index finger of each hand rhythmically, back-and-forth between a pair of targets. The ID, associated with the task performed by each hand, was
Twan ten Haaf, Selma van Staveren, Danilo Iannetta, Bart Roelands, Romain Meeusen, Maria F. Piacentini, Carl Foster, Leo Koenderman, Hein A.M. Daanen and Jos J. de Koning
computerized finger-precuing task, 14 a test modified from the test as described by Miller 15 (Figure 2 ). Each task started with the warning sign displayed on a computer screen: 4 plus signs on a row (+ + + +), which indicated the 4 possible target locations on the keyboard (left middle finger, left index
Howard N. Zelaznik
timekeepers at one timing task would be consistent timekeepers at other timing tasks. Robertson et al. ( 1999 ) required research participants to perform a finger tapping task at each of four metronome periods: 325, 400, 475, and 550 ms. In addition, these participants also performed a circle-drawing timing
Mark L. Latash
defined at the highest level of the hierarchy (e.g., at the level of the index finger during pointing or the tip of the hammer moved by the blacksmith). Further, it produces RCs at hierarchically lower levels such as those of individual joints, muscles, and MUs. This sequence of few-to-many mappings
Mark L. Latash
this problem with the task of reaching a target with an arm. A spatial target can be described with three coordinates, while there are at least seven main axes of joint rotation in the human arm (even if one does not count scapular motion and finger motion). To perform a reaching movement the person