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Analysis of movement of a disabled person from wheelchair to car seat
Abstracts / Gait & Posture 30S (2009) S26–S74
simple experimental protocols and models cannot describe such complex systems. The discrepancy between the results of the two experiments suggest some careful on data interpretation. References [1] Iacoboni M, Dapretto M. Nat Rev Neurosci 2006;7:942–51. [2] Cattaneo L, et al. PNAS USA 2007;104:17825–30.
doi:10.1016/j.gaitpost.2009.07.063 The Mirror-Neuron System Paradigm and its consistency P.B. Pascolo ∗ , P. Ragogna, R. Rossi University of Udine - Industrial Bioengineering Laboratory, Udine, Italy Introduction: The mirror neurons had an immediate success to explain complex issues in many fields, such as autism and action understanding, leading to e.g. new rehabilitation protocols. An analysis of the literature on mirror neurons points out that the majority of the articles concerns reviews while just few concerns reliable experiments, that is neuro-physiological studies on monkeys. It is worth stressing that there exists a copious literature on the function of neurons and the brain in general which shows disinterest in the paradigm. Indeed the first author reporting the existence of a group of neurons that fire during action observation did not carry any other research on them [1,2]. Therefore seminal experiments on monkeys [3,4] have been re-analyzed (in particular the neural spikes during the observation and the execution of motor acts), and the methodology and interpretation of experimental results obtained by researchers are discussed. The first announce of the mirror neuron paradigm comes from Rizzolatti et al. [4]. Methods: In a hypothetical recording of neural activity, one would register bioelectrical activity that was in anticipation (preparation of the motor action), delayed or synchronized in one individual with respect to the other. Every single recording of the activity relative to the neuron in Fig. 1a [4] was considered, both in number of firings and in temporal distance between the first and last registered firing, and it was placed in relation with the vertical segment which aligns the achievements of the target by the experimenter. The median of fires is indicated in red, and the average time in blue. Results: Examine Fig. 1a from the work of Rizzolatti et al. [4]. The start of the trials is represented by a spot in bold type. The vertical segment indicates the experimenter’s attainment of the food. Observe the “tendency line”: regarding the aligning segment the neuron seems having “improving capabilities”. It can improve
Fig. 1. (a) Visual and motor responses of a grasping mirror neuron. A tray with a piece of food was presented to the monkey, the experimenter made the grasping movement toward the food and then moved the food and the tray toward the monkey who grasped it. Rasters and histograms are aligned with the moment at which the experimenter touched the food either with his hand or with the pliers (vertical line), [is] Histogram bill width: 20 ms. Ordinates, spikes/lin; abscissae, time.
S65
only if the experimenter starts the grasping action during the presentation of the tray of food, that is, very quickly (see figure), but in the work it is stated that the presentation of the food on the tray comes first, in order to show that the neuron does not fire. At any rate, not repetitive and improvised behaviour would influence or frighten the animal and would, therefore, interfere with the response. This reasoning brings the hypothesis that the neuron had started firing even before the experimenter’s movement. Moreover the neuron in the trial in question (see figure), seem to complete the “virtual” precision grip around 0.25 s before the experimenter, that is, it anticipates the experimenter’s actions. Why is it so labeled as “mirror”? If the neuron anticipates the action we cannot speak about the “imitation” paradigm. Discussion: A boxer on the defensive has to anticipate his opponent’s action in order to avoid the hit. Attack and defence actions, including those involving trunk movement, occur within 200 ms. Therefore it is not by a mirroring process of his opponent’s gesture that he is able to avoid the blow: perhaps it is an expression on the opponent’s face, gesture or position of his body, the action he had previously performed or all of these and other aspects put together [5,6]. With these new considerations the concept of mirror neurons needs to be radically revised. It is concluded that experiments reviewed in this work recognized the function undertaken in a certain time from a group of neurons, instead of a neuron property that allows to recognize a class of neurons.
References [1] [2] [3] [4] [5]
Di Pellegrino G. Trends in Cognitive Sciences 2001;5:100. Moretto G, Di Pellegrino G. Experimental Brain Research 2008;188:505–15. Di Pellegrino G, et al. Experimental Brain Research 1992;91:176–80. Rizzolatti G, et al. Cognitive Brain Research 1996;3:131–41. Carniel R, Del Pin E, Budai R, Pascolo P. Chaos Solitons and Fractals 2005;23:1259–66. [6] Pascolo P, Barazza F, Carniel R. Chaos Solitons and Fractals 2006;27:1339–46.
doi:10.1016/j.gaitpost.2009.07.064 Analysis of movement of a disabled person from wheelchair to car seat P. Ragogna ∗ , R. Rossi, P.B. Pascolo University of Udine - Industrial Bioengineering Laboratory, Udine, Italy Introduction: For a disabled person the access to the vehicle is a critical moment in which he loses part of the autonomy achieved becoming, especially in the case of quadriplegia, completely dependent on the accompanist. In this study a kinematic analysis of the transition phase from wheelchair to car seat, performed by people with spinal cord injuries, has been conducted. Precedent studies have already assessed the transfer between two seats (e.g. [1]), but never with reference to the vehicle. The aim is to obtain information useful for optimization of the movement strategies and for ergonomics in design of assistive devices. Methods: The study was conducted in ten disabled person (eight paraplegic and two quadriplegic) who were asked to seat into the driver’s seat of a vehicle from their own wheelchair. As controls, ten healthy subjects were also evaluated during normal entering in the car. The motion analysis was performed with the optokinetic system AC-Motion, developed at the Industrial Bioengineering Laboratory, of University of Udine [2,3]. This system uses passive markers applied on body landmarks, a digital camera for motion acquisition (performed at 30 fps) and software developed in MatLab environment for the analysis of movement.
S66
Abstracts / Gait & Posture 30S (2009) S26–S74
Results: The results were reported in terms of execution time of the maneuver, trajectories of body parts and angular velocity of the trunk. The analysis of the trajectories of shoulder, elbow and wrist led to an initial estimate of the space required by the gesture and highlighted the areas of the vehicle on which the subject leaned on during the maneuver (figure on left). Tests on healthy subjects did not show significant differences in terms of position and angular velocity of the trunk. Instead in the case of disabled people the gesture was greatly affected by pathology (i.e. level of cord injury) and by consequent remaining ability. From the comparison of angular velocity (figure on right) it is evident the degradation of gesture in the case of a subject with spinal injury, in terms of greater angular velocity and more interruptions in the movement.
Discussion: This protocol of investigation helps to identify the location of any critical issues in the movement and permit to guide the choice of correct assistive device and the most effective rehabilitation treatment. Execution times and measured velocity allow considerations on the fibers recruited, on muscle fatigue and on the ability to repeat the gesture when needed. It was found that the movement is influenced by the individual’s remaining ability, by any assistive device eventually available and by the kind of vehicle. All these three aspects are strongly interlinked: for example the type of vehicle influences the assistive device installable, which in turn must be chosen considering the remaining capacity of the disabled.
A system for real-time mapping of foot segment pressures in dynamic posturography J.L. Jackson 1,2,∗ , P. Cappa 1,2 , F. Patanè 1,2 , M. Petrarca 2 1
“Sapienza” University of Rome, Rome, Italy Children’s Hospital “Bambino Gesù” IRCCS, Passoscuro (Fiumicino) Rome, Italy 2
Introduction: A pressure-mapping system (PMS) was developed to evaluate the shifts of center of pressure (COP) within the segments of the foot while trying to maintain equilibrium during perturbed standing. The PMS includes a multi-sensor pressure array capable of programmatically identifying the segments of the foot (toes, sole, midfoot, and heel) and characterizing the COP for each. Previous pressure-mapping studies conducted required offline segmentation and data analysis [1,2]. We propose this system as a unique tool to provide real-time, high resolution pressure information for use in dynamic posturography studies once integrated with an ad hoc spherical robot (SR) currently in use in the laboratory. Materials and Methods: The design requirements for the PMS were the following: real-time data acquisition of pressure data, automatic detection and segmentation of each foot as described in Fig. 1 without operator intervention, calculation of COP and coordinates the related anteroposterior (A-P) and mediolateral (M-L) coordinates for each segment, and export of calculated data to the SR’s controller. To ensure subject safety, it was imperative that the interaction between the PMS and the SR not interrupt or disable the operation of the SR during use. Therefore, the PMS was designed with little dependency on the SR control functions. The characteristics of the SR are thoroughly described in a previous article [3] and patent [4]. The plantar pressure measurement system is comprised of a MatScan® sensorized pressure mat (Tekscan, Inc., Boston, MA, USA) and a software interface developed in LabVIEWTM 8.2.1 (National Instruments, Inc. Austin, TX, USA). The interface collects raw pressure measurements from the acquisition system, performs the necessary calculations, and transmits the data to the platform controller to be synchronized with other measurements. A pilot study was conducted to verify the initial design requirements by validating the pressure measurements and the calculated coordinates. A subject was instructed to stand quietly on the pressure mat while performing a reaching task in three directions: to the subject’s right, left, and front. Both the Matscan® commercial software and the LabVIEWTM system collected the data from the pressure mat. The Matscan® commercial system served as the reference since it has already been validated for balance studies [1,2]. Results: The PMS results were examined for errors for each detected foot segment. Fig. 2 shows the average discrepancy between the Matscan® software analysis and that computed by the LabVIEWTM program. The average error for the COP pressure measurements for all foot segments was between 2 and 4% of total COP applied to the segment area with the toe segments having the most variability between the two analysis packages.
References [1] Gagnon D, et al. Clinical Biomechanics 2008;23:279–90. [2] Cappellazzo A. Master Thesis, University of Udine, Academic Year 1999/00. [3] Bolzan A. Master Thesis, University of Udine, Academic Year 2008/09.
doi:10.1016/j.gaitpost.2009.07.065
Fig. 1. PMS-detected foot segments (right foot shown as example).
simple experimental protocols and models cannot describe such complex systems. The discrepancy between the results of the two experiments suggest some careful on data interpretation. References [1] Iacoboni M, Dapretto M. Nat Rev Neurosci 2006;7:942–51. [2] Cattaneo L, et al. PNAS USA 2007;104:17825–30.
doi:10.1016/j.gaitpost.2009.07.063 The Mirror-Neuron System Paradigm and its consistency P.B. Pascolo ∗ , P. Ragogna, R. Rossi University of Udine - Industrial Bioengineering Laboratory, Udine, Italy Introduction: The mirror neurons had an immediate success to explain complex issues in many fields, such as autism and action understanding, leading to e.g. new rehabilitation protocols. An analysis of the literature on mirror neurons points out that the majority of the articles concerns reviews while just few concerns reliable experiments, that is neuro-physiological studies on monkeys. It is worth stressing that there exists a copious literature on the function of neurons and the brain in general which shows disinterest in the paradigm. Indeed the first author reporting the existence of a group of neurons that fire during action observation did not carry any other research on them [1,2]. Therefore seminal experiments on monkeys [3,4] have been re-analyzed (in particular the neural spikes during the observation and the execution of motor acts), and the methodology and interpretation of experimental results obtained by researchers are discussed. The first announce of the mirror neuron paradigm comes from Rizzolatti et al. [4]. Methods: In a hypothetical recording of neural activity, one would register bioelectrical activity that was in anticipation (preparation of the motor action), delayed or synchronized in one individual with respect to the other. Every single recording of the activity relative to the neuron in Fig. 1a [4] was considered, both in number of firings and in temporal distance between the first and last registered firing, and it was placed in relation with the vertical segment which aligns the achievements of the target by the experimenter. The median of fires is indicated in red, and the average time in blue. Results: Examine Fig. 1a from the work of Rizzolatti et al. [4]. The start of the trials is represented by a spot in bold type. The vertical segment indicates the experimenter’s attainment of the food. Observe the “tendency line”: regarding the aligning segment the neuron seems having “improving capabilities”. It can improve
Fig. 1. (a) Visual and motor responses of a grasping mirror neuron. A tray with a piece of food was presented to the monkey, the experimenter made the grasping movement toward the food and then moved the food and the tray toward the monkey who grasped it. Rasters and histograms are aligned with the moment at which the experimenter touched the food either with his hand or with the pliers (vertical line), [is] Histogram bill width: 20 ms. Ordinates, spikes/lin; abscissae, time.
S65
only if the experimenter starts the grasping action during the presentation of the tray of food, that is, very quickly (see figure), but in the work it is stated that the presentation of the food on the tray comes first, in order to show that the neuron does not fire. At any rate, not repetitive and improvised behaviour would influence or frighten the animal and would, therefore, interfere with the response. This reasoning brings the hypothesis that the neuron had started firing even before the experimenter’s movement. Moreover the neuron in the trial in question (see figure), seem to complete the “virtual” precision grip around 0.25 s before the experimenter, that is, it anticipates the experimenter’s actions. Why is it so labeled as “mirror”? If the neuron anticipates the action we cannot speak about the “imitation” paradigm. Discussion: A boxer on the defensive has to anticipate his opponent’s action in order to avoid the hit. Attack and defence actions, including those involving trunk movement, occur within 200 ms. Therefore it is not by a mirroring process of his opponent’s gesture that he is able to avoid the blow: perhaps it is an expression on the opponent’s face, gesture or position of his body, the action he had previously performed or all of these and other aspects put together [5,6]. With these new considerations the concept of mirror neurons needs to be radically revised. It is concluded that experiments reviewed in this work recognized the function undertaken in a certain time from a group of neurons, instead of a neuron property that allows to recognize a class of neurons.
References [1] [2] [3] [4] [5]
Di Pellegrino G. Trends in Cognitive Sciences 2001;5:100. Moretto G, Di Pellegrino G. Experimental Brain Research 2008;188:505–15. Di Pellegrino G, et al. Experimental Brain Research 1992;91:176–80. Rizzolatti G, et al. Cognitive Brain Research 1996;3:131–41. Carniel R, Del Pin E, Budai R, Pascolo P. Chaos Solitons and Fractals 2005;23:1259–66. [6] Pascolo P, Barazza F, Carniel R. Chaos Solitons and Fractals 2006;27:1339–46.
doi:10.1016/j.gaitpost.2009.07.064 Analysis of movement of a disabled person from wheelchair to car seat P. Ragogna ∗ , R. Rossi, P.B. Pascolo University of Udine - Industrial Bioengineering Laboratory, Udine, Italy Introduction: For a disabled person the access to the vehicle is a critical moment in which he loses part of the autonomy achieved becoming, especially in the case of quadriplegia, completely dependent on the accompanist. In this study a kinematic analysis of the transition phase from wheelchair to car seat, performed by people with spinal cord injuries, has been conducted. Precedent studies have already assessed the transfer between two seats (e.g. [1]), but never with reference to the vehicle. The aim is to obtain information useful for optimization of the movement strategies and for ergonomics in design of assistive devices. Methods: The study was conducted in ten disabled person (eight paraplegic and two quadriplegic) who were asked to seat into the driver’s seat of a vehicle from their own wheelchair. As controls, ten healthy subjects were also evaluated during normal entering in the car. The motion analysis was performed with the optokinetic system AC-Motion, developed at the Industrial Bioengineering Laboratory, of University of Udine [2,3]. This system uses passive markers applied on body landmarks, a digital camera for motion acquisition (performed at 30 fps) and software developed in MatLab environment for the analysis of movement.
S66
Abstracts / Gait & Posture 30S (2009) S26–S74
Results: The results were reported in terms of execution time of the maneuver, trajectories of body parts and angular velocity of the trunk. The analysis of the trajectories of shoulder, elbow and wrist led to an initial estimate of the space required by the gesture and highlighted the areas of the vehicle on which the subject leaned on during the maneuver (figure on left). Tests on healthy subjects did not show significant differences in terms of position and angular velocity of the trunk. Instead in the case of disabled people the gesture was greatly affected by pathology (i.e. level of cord injury) and by consequent remaining ability. From the comparison of angular velocity (figure on right) it is evident the degradation of gesture in the case of a subject with spinal injury, in terms of greater angular velocity and more interruptions in the movement.
Discussion: This protocol of investigation helps to identify the location of any critical issues in the movement and permit to guide the choice of correct assistive device and the most effective rehabilitation treatment. Execution times and measured velocity allow considerations on the fibers recruited, on muscle fatigue and on the ability to repeat the gesture when needed. It was found that the movement is influenced by the individual’s remaining ability, by any assistive device eventually available and by the kind of vehicle. All these three aspects are strongly interlinked: for example the type of vehicle influences the assistive device installable, which in turn must be chosen considering the remaining capacity of the disabled.
A system for real-time mapping of foot segment pressures in dynamic posturography J.L. Jackson 1,2,∗ , P. Cappa 1,2 , F. Patanè 1,2 , M. Petrarca 2 1
“Sapienza” University of Rome, Rome, Italy Children’s Hospital “Bambino Gesù” IRCCS, Passoscuro (Fiumicino) Rome, Italy 2
Introduction: A pressure-mapping system (PMS) was developed to evaluate the shifts of center of pressure (COP) within the segments of the foot while trying to maintain equilibrium during perturbed standing. The PMS includes a multi-sensor pressure array capable of programmatically identifying the segments of the foot (toes, sole, midfoot, and heel) and characterizing the COP for each. Previous pressure-mapping studies conducted required offline segmentation and data analysis [1,2]. We propose this system as a unique tool to provide real-time, high resolution pressure information for use in dynamic posturography studies once integrated with an ad hoc spherical robot (SR) currently in use in the laboratory. Materials and Methods: The design requirements for the PMS were the following: real-time data acquisition of pressure data, automatic detection and segmentation of each foot as described in Fig. 1 without operator intervention, calculation of COP and coordinates the related anteroposterior (A-P) and mediolateral (M-L) coordinates for each segment, and export of calculated data to the SR’s controller. To ensure subject safety, it was imperative that the interaction between the PMS and the SR not interrupt or disable the operation of the SR during use. Therefore, the PMS was designed with little dependency on the SR control functions. The characteristics of the SR are thoroughly described in a previous article [3] and patent [4]. The plantar pressure measurement system is comprised of a MatScan® sensorized pressure mat (Tekscan, Inc., Boston, MA, USA) and a software interface developed in LabVIEWTM 8.2.1 (National Instruments, Inc. Austin, TX, USA). The interface collects raw pressure measurements from the acquisition system, performs the necessary calculations, and transmits the data to the platform controller to be synchronized with other measurements. A pilot study was conducted to verify the initial design requirements by validating the pressure measurements and the calculated coordinates. A subject was instructed to stand quietly on the pressure mat while performing a reaching task in three directions: to the subject’s right, left, and front. Both the Matscan® commercial software and the LabVIEWTM system collected the data from the pressure mat. The Matscan® commercial system served as the reference since it has already been validated for balance studies [1,2]. Results: The PMS results were examined for errors for each detected foot segment. Fig. 2 shows the average discrepancy between the Matscan® software analysis and that computed by the LabVIEWTM program. The average error for the COP pressure measurements for all foot segments was between 2 and 4% of total COP applied to the segment area with the toe segments having the most variability between the two analysis packages.
References [1] Gagnon D, et al. Clinical Biomechanics 2008;23:279–90. [2] Cappellazzo A. Master Thesis, University of Udine, Academic Year 1999/00. [3] Bolzan A. Master Thesis, University of Udine, Academic Year 2008/09.
doi:10.1016/j.gaitpost.2009.07.065
Fig. 1. PMS-detected foot segments (right foot shown as example).