| | The Effect of Visual Biofeedback on the Propulsion Effectiveness of Experienced Wheelchair UsersAbstract Kotajarvi BR, Basford JR, An K-N, Morrow DA, Kaufman KR. The effect of visual biofeedback on the propulsion effectiveness of experienced wheelchair users. ObjectiveTo determine the effect of visual feedback on the propulsion effectiveness of experienced manual wheelchair users. SettingA motion analysis laboratory. ParticipantsA convenience sample of 16 healthy men and 2 healthy women with T4-L2 traumatic paraplegia, a mean age of 38±9 years, and a mean duration of manual wheelchair-based mobility of 14±8 years. InterventionPropulsion was assessed as the subjects propelled an instrumented wheelchair (with and without visual biofeedback) on a custom-built dynamometer at propulsion intensities of .15 and .25W/kg for 10 minutes. Main Outcome MeasuresThe primary outcome variable was the fraction of effective force (FEF) (ie, the ratio of effective to total force) applied by the subject to the wheelchair’s pushrim. Secondary variables included velocity, stroke frequency, and stroke angle. ResultsA 2-factor analysis of variance with repeated measurements was used to detect significant differences between the outcome variables. The FEF ratio was 73.9% without feedback and 72.5% with feedback at the lower-intensity level. Propulsion during the higher intensity condition both with and without feedback resulted in a statistically significant improvement in the FEF (73.9%–78.7% with no feedback, 72.5%–80.2% with feedback), compared with the lower-intensity level. Stroke angle increased from 84.3° to 98.7° and frequency decreased from 66 to 57.8 strokes/min with feedback. ConclusionsVisual biofeedback may have little utility in improving the force effectiveness of manual wheelchair propulsion in experienced wheelchair users. Experienced wheelchair users may have already optimized their stroke in a manner that balances energy expenditure with stroke efficiency. Other variables such as stroke length and frequency may be more amenable to visual biofeedback.
DURING THE PAST FEW YEARS, the study of wheelchair propulsion has become popular as the technology to gather information on biomechanic parameters has improved. The assumption that high mechanical loads on the upper extremity are a major causative factor in the development of pain in the upper extremity is a driving force behind this trend. In particular, shoulder pain is the most documented upper-extremity problem associated with wheelchair use and has been reported to have a prevalence rate of 30% to 50%.1, 2, 3, 4, 5, 6 Wheelchair handrim propulsion has been characterized as a relatively inefficient mode of propulsion when compared with other methods such as arm-cranking. The mechanical efficiency of propulsion has been calculated using the ratio between power output and oxygen cost under submaximal, physiologic steady-state conditions. This ratio ranges from 2% to 10%.7, 8, 9 In contrast, arm-cranking values using an ergometer or hand-bike can range up to 15%.10, 11 Specialized equipment is needed to calculate mechanical efficiency, such as oxygen uptake equipment and specialized wheelchair ergometers or treadmills. As an alternative to measuring mechanical efficiency, investigators have measured the effectiveness of force application in wheelchair propulsion using force components that are measured at the pushrim with an instrumented wheel.12, 13, 14, 15, 16, 17, 18, 19 The low mechanical efficiency of propulsion was thought to be due in some part to the low effectiveness of force application on the rim.20, 21 These measures, which can be more correctly identified not as efficiency, but as effectiveness measures, usually take 1 of 2 forms, the mechanical effective force (MEF), and fraction of effective force (FEF). The MEF is the proportion of force at the pushrim that contributes to forward motion and is defined as Ft2/F2×100, where Ft is the tangential force obtained by dividing the measured wheel torque by the radius of the pushrim, and F is the resultant force. The FEF uses the same definition without squaring both numerator and denominator. Because the tangential force is the only force which drives the wheelchair forward, higher FEF and MEF values imply more effective application of force. Values reported in the literature range from 50% to 80% depending on the subjects (wheelchair users vs able-bodied).13, 16, 17, 22, 23 With the adoption of this measurement methodology, research has been directed at attempts to raise the effectiveness of wheelchair propulsion via training. For instance, Dallmeijer et al24 looked at the effects of a 7-week wheelchair training program on 19 male able-bodied subjects consisting of 30 minutes of exercise, 3 times a week, at 50% and 70% of the individual heart rate reserve, on a number of biomechanic variables including force effectiveness using the FEF. Results showed that wheelchair training in inexperienced subjects did not have an effect on force application compared with a control group. Some changes in timing and stroke parameters did improve in the training group, such as an increased push time and stroke angle, and decreased stroke frequency. De Groot et al25 had similar results in a study which employed a 3-week training program and 10 able-bodied subjects. Based on these results, de Groot hypothesized that the 3- and 7-week training programs were either too short to elicit changes, or that adaptations in the effectiveness of force application take place relatively quickly during the first few seconds or minutes of practice. Along these lines, 9 able-bodied subjects performed three 4-minute practice blocks on a wheelchair ergometer to study short-term adaptations. Again, no differences were found over time for the FEF. In fact, these novice subjects immediately reached an FEF of 70% to 80%.26 In further attempts to improve force effectiveness de Groot investigated the effects of visual feedback on both the FEF and mechanical efficiency. Ten able-bodied male subjects propelled on a wheelchair ergometer 3 times a week for 3 weeks while receiving visual feedback on velocity and the FEF. Compared with a control group of 10 subjects who did not receive feedback, the experimental group had a significantly higher FEF (90%–97% vs 79%–83%), but showed significantly lower mechanical efficiency (5.5%–8.5% vs 5.9%–9.9%).25 From this data it was concluded that the most effective force production from a mechanical point of view was not compatible with minimizing energy cost from a biologic point of view. In other words, the direction of force is already optimal given the constraints of handrim propulsion.25 This challenges the assumption that a low FEF or effectiveness of force is responsible for the low mechanical efficiency of wheelchair propulsion.
To add to the body of knowledge on this topic, we examined the effects of visual feedback on the FEF. We used a group of 18 experienced wheelchair users as subjects, in contrast to de Groot, who used able-bodied subjects who had no experience with wheelchair propulsion, because we were curious as to whether propulsion effectiveness could be improved in a population that had experience with the task. Also, if our results were favorable, this would be the target population to enhance this skill and increase the effectiveness of propulsion. In addition, we were curious as to the effect of propelling at a higher intensity level on the FEF. The effectiveness of force application was shown to be greater at a higher intensity level in a previous study.16 Our hypothesis was that both visual feedback and a higher intensity workload would increase the FEF.
Methods  Participant Recruitment The Mayo Institutional Review Board reviewed the protocol. After protocol approval, we identified wheelchair users from our rehabilitation unit database and sent a letter describing the study and requesting their participation. Additional recruitment was accomplished via word of mouth and advertisements posted on bulletin boards in local accessible housing units. Inclusion criteria included: use of a manual wheelchair as the primary mode of mobility, an injury level below the T4 level, and at least 6 months of experience in wheelchair propulsion. Exclusion criteria included: current or chronic upper-extremity pain, a history of a significant upper-extremity injury, involvement in competitive sports with a specific training program, or employment in an occupation that required repetitive use of the upper extremities in an elevated position. We interviewed each subject, to familiarize them with the protocol and to determine if the inclusion and exclusion criteria were satisfied. Data Collection Subjects completed a brief demographic questionnaire on arrival in the laboratory. Body weight was determined by subtracting the weight of the subject’s empty chair from the weight of the chair with the subject in place. Height was self-reported. Subjects then transferred to an Action Pro-SA lightweight sport wheelchaira with a custom-built instrumented wheel on the right side. The instrumented wheel included a 6-component load cellb mounted on the pushrim, which provided the 3 orthogonal components of the forces and moments applied to the pushrim. This wheel has been previously used in our laboratory to collect kinetic data during wheelchair propulsion.27, 28 The study wheelchair’s back height and footrests were adjusted to the subject’s preference and the chair was positioned on the wheelchair dynamometer. The dynamometer (fig 1) consisted of an elevated platform on which the rear wheels of the wheelchair rest against a single 38.1-cm (15-in) diameter drum. Inertia is provided by a 22.7-kg (50-lb) flywheel. The subject provided all of the work to turn the wheels of the chair using this system. A locking mechanism secured the wheelchair to the dynamometer in a manner that prevented adventitious loading of the drum. Safety railings surrounded the platform and provided support for a monitor displaying visual feedback data. A computer system was mounted beneath the platform for collecting and processing kinetic data. A friction brake provided mechanical resistance to adjust the ease or difficulty of propulsion to those required by the experiment. Subjects acclimated to the dynamometer by pushing at a self-selected speed until they were comfortable with the experimental setup. After this warm-up period, each subject propelled at a target speed of 1.2m/s for 4 trials. Each trial lasted approximately 10 minutes with 5 minutes of rest between trials. The first 2 trials took place at an external power output of .15W/kg of body weight. The second 2 were at an output of .25W/kg and were conducted on a separate day so that fatigue would not influence the results. Power output and velocity of the right wheel was measured in real time with a custom-developed LabViewc program. Resistance to propulsion was either increased or decreased by adjusting a frictional brake. The video feedback monitor provided immediate feedback on the FEF, velocity, and power output during the push phase of propulsion. Feedback was provided only for the second trial of each set. Subjects were told that the FEF curve on the monitor represented a measure of how well they pushed the chair. They were instructed to attempt to increase the height of the FEF curve but were not told that it represented production of tangential force. No further instruction was given to the subjects. Data collection was initiated when the subject reached the target velocity and continued for the remainder of the trial. Kinetic Data Analysis Force and moment data that are measured at the wheel axle were collected at a frequency of 50Hz. The global coordinate system of the wheel was defined as follows: Fx, horizontally forward; Fy, horizontally outward; and Fz, vertically downward. From these force components the total force applied to the pushrim was calculated as follows:
The effective component of the propulsion force which drives the wheels forward (F eff) was calculated from the torque around the wheel axle (M) and pushrim radius (r r) according to:
The FEF ratio on the handrim was then calculated from the above equations and expressed as a percentage:
This method of calculation, which has also been used by de Groot et al,25, 26 assumes that a propulsive force is applied by the hand, not a torque. If a positive torque is provided by the hand, then FEF values in excess of 100% are possible. The beginning of the propulsive phase of the cycle was identified by a minimum effective force of 5N. For each trial, a minimum of 30 strokes were used for data analysis, which was equal to about 30 seconds of propulsion toward the end of their 10-minute trial. The following variables were calculated using a custom Matlabd program: velocity, total force, effective force, mean FEF, stroke frequency, and stroke angle. Peak resultant and effective force values were obtained for each propulsive stroke and the mean of these peak values was then calculated. The FEF similarly is an average of a number of propulsive strokes; however, the mean value of all data points during the push phase of the cycle is used, as opposed to the peak value. Statistical Analysis Statistical analyses were performed using SAS software.e A 2-factor analysis of variance with repeated measurements was used to detect significant differences for the biomechanic variables. The main independent effects of external power output (.15W/kg, .25W/kg) and visual feedback (presence, absence) were assessed along with the interaction of these 2 factors. Post hoc analysis tests consisted of the Student-Newman-Keuls multiple range tests for all main effect means. Significance level was set at P less than .05 for all statistical procedures. Results Effect of Visual Feedback The effects of visual feedback on the force and timing variables at the 2 propulsion intensity levels are displayed in table 2. Propulsion velocity was higher with visual feedback but only at the .15-W/kg power level. Pushrim force values did not significantly change with feedback at either intensity level. Stroke frequency decreased and stroke angle increased with feedback. The mean FEF did not change with feedback at either intensity level (see fig 2). There were no interaction effects between the variables of power and feedback for any of the variables with the exception of velocity. Discussion The intent of this study was to examine the effects of both visual feedback and intensity level on the effectiveness of force production during handrim wheelchair propulsion in a sample of experienced wheelchair users. Our results showed that the mean FEF during the push phase of the stroke did not improve when subjects were given visual feedback. This finding conflicts with the results of de Groot et al25 who found an FEF which ranged from 90% to 97% (depending on the power output) in an experimental group, compared with 79% to 83% for a control group. There are important differences between our study and de Groot’s with respect to subjects and methodology. Both the experimental and control group in their study consisted of able-bodied subjects without any experience in wheelchair propulsion. Also, their experimental group practiced for 8 minutes 3 times a week for 3 weeks. Therefore, they spent a total of 72 minutes on the ergometer receiving visual feedback, in contrast to the relatively short time interval in our study. Perhaps with greater time devoted to the task, our subjects might have shown an improvement. On the other hand, because biomechanic measurements were only taken during the last session of their study, it is not known what effect the length of practice time has on the FEF. It is also possible that able-bodied persons are able to learn to improve their effectiveness of force production, while those with paraplegia cannot. Subjects engaged in all types of alterations to their stroke in attempts to increase the height of the FEF curve. After the feedback trial, subjects were questioned as to what they thought increased the height of the curve. Many thought that leaning forward and directing the stroke in a downward direction resulted in a higher curve. This would have the effect of increasing the force tangential to the pushrim. However, these same users also reported that it was fatiguing and difficult to maintain this posture for any length of time. This most likely would be due to the constraints that impaired motor control places on their trunk stability. This theory is in agreement with the finding from de Groot’s study that although the able-bodied subjects in the experimental group were able to improve the effectiveness of force production, they did so at a higher metabolic cost, as their mechanical efficiency was significantly lower when compared with the control group. This suggests that the most effective means of force production from a mechanical point of view is not the most efficient from an energy cost standpoint. Ultimately the direction of force is likely based on achieving a balance between energy cost and force effectiveness. The results also showed that stroke angle increased and stroke frequency decreased during the visual feedback trials. With a longer stroke and more time spent on the rim, the frequency of propulsion (strokes per minute) can be decreased while maintaining the target velocity. On questioning, subjects reported that this was another strategy employed in an attempt to increase the magnitude of the FEF curve. Because the mean FEF was not higher during visual feedback, this strategy was not successful. This does not mean that using longer strokes is not advantageous. Previous research has shown that higher stroke frequency (shorter and more rapid strokes) correlates with injury to the median nerve.29 Boninger et al30 advocated adjustments to the wheelchair that resulted in a shorter vertical distance between the axle and shoulder and a forward axle position which result in a higher push angle and lower stroke frequency. These variables were associated with an improvement in propulsion biomechanics such as a decrease in the rate of rise of the resultant force. In summary, the hypothesis that visual feedback will improve the effectiveness of force production is rejected. In addressing our second hypothesis, we found that propelling at a higher workload resulted in an improvement in the FEF (72.5%–80.2%). This finding is in agreement with Dallmeijer et al16 who found the effectiveness of force application to significantly increase with a higher workload. De Groot et al,31 in a study that examined the influence of task complexity on mechanical efficiency and propulsion technique during the learning of handrim wheelchair propulsion, found that an increase in the power output of 1W led to a 6% increase in the FEF. Similarly, our data indicate that an increase in the intensity level of 1W led to an 8% increase in the FEF. At a higher intensity level, the application of a tangential force becomes more critical, and a greater proportion of this force in relation to the total force must be applied to keep the wheels turning. This could be thought of outside of the laboratory as the extra effort and attention to propulsion technique that is necessary when a wheelchair user ascends a steep ramp. De Groot25 also reached this conclusion by stating that under low submaximal conditions propulsion technique is less critical to performance and therefore differences in the effectiveness of force production may be seen only at higher intensities. Although data analysis showed a statistically significant increase in the FEF at the higher intensity level, we do not feel that this increase of 6% constitutes a clinically meaningful difference. Given the results of this study, we have to question whether it is reasonable to devote time and effort to the task of trying to improve the effectiveness of force production during wheelchair propulsion. Subjects in our study could exclusively focus on propulsion technique without being concerned with steering corrections or other environmental distractions due to the fact they were propelling on a stationary ergometer, and still could not improve their force effectiveness with feedback. If improvement does occur as it did with able-bodied subjects in de Groot’s study, it comes at the expense of a higher metabolic cost. Or in other words, a higher FEF does not lead to higher mechanical efficiency measurements.25 Because improvements in mechanical efficiency suggest better control and learning of the motor task or improved “economy of movement,” we need to strongly consider that the effectiveness of force production cannot be further optimized. Because our subjects were experienced users, it is likely that their neuromuscular control system has adapted to their injury and that force is being delivered in a manner which results in a minimization of energy loss. They could deliver more tangentially directed force, but their body knows that this will take more energy. Consequently, it does not seem appropriate to focus on improving the FEF for purposes of training or learning. On the other hand, this does not mean that some other forms of instruction cannot be beneficial. Instruction in proper coupling of the hand to the rim to avoid injury to the median nerve is one example based on the research by Boninger et al.29 Other skills to improve mobility in the community are probably more important to learn such as maneuvering the chair in a tight space, negotiating small thresholds and curbs, and performing a wheelie to descend ramps. The stationary wheelchair ergometer may also have a role in conditioning of muscles used for propulsion in those people who have a new injury, while keeping distractions at a minimum. In this way the individual can concentrate solely on making long and smooth strokes, or develop a technique in which he/she feels most comfortable. This is probably the technique for him/her, which also is the most efficient. Study Limitations There are a number of limitations to our study. Although subjects received real time feedback on velocity, it was difficult to keep it from fluctuating during propulsion. Therefore, there were small differences in the mean velocity between the different conditions. We did not obtain any kinematic measurements during propulsion, so the point of force application on the pushrim could not be obtained. Therefore, we needed to use a simplified method to calculate the effective force component that relies on measurement of torque around the wheel axle and does not take into account the torque around the hand. This torque could become as high as 40% of the total propulsion torque but previous research has shown that it is generally directed against the propulsion torque for most of the push phase.32, 33 The relatively low number of subjects in this study also means that the possibility of incurring a type II error should be considered. Finally, subjects did not use their own wheelchair on the ergometer. Although the backrest and footrest heights were individually adjusted to the dimensions of their personal chair, there may have been other characteristics, such as camber angle and seat width, that could not be replicated. Conclusions This study found no change in the FEF when experienced wheelchair users received real time visual feedback. We speculated that experienced users have already optimized their stroke and could only improve their FEF at the expense of using more energy by substantially altering their stroke technique. In addition, the FEF significantly improved when propelling at a higher intensity level which emphasizes the need for increased attention to technique when a greater workload is imposed on the activity. Improvement in the FEF should not be considered a goal during the training of wheelchair propulsion. Other training interventions such as improving stroke length and decreasing stroke frequency to decrease force on the pushrim may be of greater value. Further research is needed to determine if training involving biofeedback can improve propulsion biomechanics and reduce upper-extremity pain and injury. Suppliers
References 1.
1
Sie IH
, Waters RL
, Adkins RH
, Gellman H
.
Upper extremity pain in the post rehabilitation spinal cord injured patient
.
Arch Phys Med Rehabil
. 1992;73:44–48
.
MEDLINE 2.
2
Subbarao JV
, Klopfstein J
, Turpin R
.
Prevalence and impact of wrist and shoulder pain in patients with spinal cord injury
.
J Spinal Cord Med
. 1995;18:9–13
.
MEDLINE 3.
3
Silfverskiold J
, Waters RL
.
Shoulder pain and functional disability in spinal cord injury patients
.
Clin Orthop Rel Res
. 1991;272:141–145
.
4.
4
Nichols PJ
, Norman PA
, Ennis JR
.
Wheelchair user’s shoulder? Shoulder pain in patients with spinal cord lesions
.
Scand J Rehabil Med
. 1979;11:29–32
.
MEDLINE 5.
5
Curtis KA
, Black K
.
Shoulder pain in female wheelchair basketball players
.
J Orthop Sports Phys Ther
. 1999;29:225–231
.
MEDLINE 6.
6
Curtis KA
, Drysdale GA
, Lanza RD
, Kolber M
, Vitolo RS
, West R
.
Shoulder pain in wheelchair users with tetraplegia and paraplegia
.
Arch Phys Med Rehabil
. 1999;80:453–457
.
Abstract |
Full-Text PDF (752 KB)
|
CrossRef
7.
7
van der Woude LH
, de Groot G
, Hollander AP
, van Ingen Schenau GJ
, Rozendal RH
.
Wheelchair ergonomics and physiological testing of prototypes
.
Ergonomics
. 1986;29:1561–1573
.
MEDLINE |
CrossRef
8.
8
van der Woude LH
, Hendrich KM
, Veeger HE
, et al.
Manual wheelchair propulsion
(effects of power output on physiology and technique)
.
Med Sci Sports Exerc
. 1988;20:70–78
.
MEDLINE |
CrossRef
9.
9
van der Woude L
, Veeger D
, Rozendal R
, van Ingen Schenau G
, Rooth F
, van Nierop P
.
Wheelchair racing
(effects of rim diameter and speed on physiology and technique)
.
Med Sci Sports Exerc
. 1988;20:492–500
.
MEDLINE 10.
10
Sawka MN
.
Physiology of upper body exercise
.
Exerc Sport Sci Rev
. 1986;14:175–211
.
MEDLINE 11.
11
Martel G
, Noreau L
, Jobin J
.
Physiological responses to maximal exercise on arm cranking and wheelchair ergometer with paraplegics
.
Paraplegia
. 1991;29:447–456
.
MEDLINE 12.
12
Boninger ML
, Cooper RA
, Robertson RN
, Shimada SD
.
Three-dimensional pushrim forces during two speeds of wheelchair propulsion
.
Am J Phys Med Rehabil
. 1997;76:420–426
.
MEDLINE |
CrossRef
13.
13
Boninger ML
, Souza AL
, Cooper RA
, Fitzgerald SG
, Koontz AM
, Fay BT
.
Propulsion patterns and pushrim biomechanics in manual wheelchair propulsion
.
Arch Phys Med Rehabil
. 2002;83:718–723
.
Abstract | Full Text |
Full-Text PDF (87 KB)
|
CrossRef
14.
14
Brubaker CE
, Ross S
, McLaurin CA
.
Effect of seat position on hand rim force
.
Proceedings of the 5th Annual Conference on Rehabilitation Engineering
. 1982;
.
15.
15
Cooper RA
, Robertson RN
, VanSickle DP
, Boninger ML
, Shimada SD
.
Methods for determining three-dimensional wheelchair pushrim forces and moments
(a technical note)
.
J Rehabil Res Dev
. 1997;34:162–170
.
MEDLINE 16.
16
Dallmeijer AJ
, van der Woude LH
, Veeger HE
, Hollander AP
.
Effectiveness of force application in manual wheelchair propulsion in persons with spinal cord injuries
.
Am J Phys Med Rehabil
. 1998;77:213–221
.
MEDLINE |
CrossRef
17.
17
Robertson RN
, Boninger ML
, Cooper RA
, Shimada SD
.
Pushrim forces and joint kinetics during wheelchair propulsion
.
Arch Phys Med Rehabil
. 1996;77:856–864
.
Abstract |
Full-Text PDF (939 KB)
|
CrossRef
18.
18
Rozendaal LA
, Veeger DE
.
Force direction in manual wheel chair propulsion
(balance between effect and cost)
.
Clin Biomech (Bristol, Avon)
. 2000;15(Suppl 1):S39–S41
.
Abstract | Full Text |
Full-Text PDF (172 KB)
|
CrossRef
19.
19
Veeger HE
, van der Woude LH
, Rozendal RH
.
Load on the upper extremity in manual wheelchair propulsion
.
J Electromyogr Kinesiol
. 1991;1:270–280
.
CrossRef
20.
20
Veeger H
, van der Woude L
, Rozendal R
.
Within-cycle characteristics of the wheelchair push in sprinting on a wheelchair ergometer
.
Med Sci Sports Exerc
. 1991;23:264–271
.
MEDLINE 21.
21
Veeger HE
, Lute EM
, Roeleveld K
, van der Woude LH
.
Differences in performance between trained and untrained subjects during a 30-s sprint test in a wheelchair ergometer
.
Eur J Appl Physiol Occup Physiol
. 1992;64:158–164
.
MEDLINE |
CrossRef
22.
22
Veeger HE
, Hadj Yahmed M
, van der Woude LH
, Charpentier P
.
Peak oxygen uptake and maximal power output of Olympic wheelchair-dependent athletes
.
Med Sci Sports Exerc
. 1991;23:1201–1209
.
MEDLINE 23.
23
Dallmeijer AJ
, Kappe YJ
, Veeger DH
, Janssen TW
, van der Woude LH
.
Anaerobic power output and propulsion technique in spinal cord injured subjects during wheelchair ergometry
.
J Rehabil Res Dev
. 1994;31:120–128
.
MEDLINE 24.
24
Dallmeijer AJ
, van der Woude LH
, Pathuis CS
.
Adaptations in wheelchair propulsion technique after training in able-bodied subjects
.
In:
van der Woude LH
, Hopman TE
, van Kemenade CH
editor.
Biomedical aspects of manual wheelchair propulsion
(the state of the art II)
. Amsterdam: IOS Pr; 1999;p. 224–226
.
25.
25
de Groot S
, Veeger HE
, Hollander AP
, van der Woude LH
.
Consequence of feedback-based learning of an effective hand rim wheelchair force production on mechanical efficiency
.
Clin Biomech
. 2002;17:219–226
.
26.
26
de Groot S
, Veeger HE
, Hollander AP
, van der Woude LH
.
Adaptations in physiology and propulsion techniques during the initial phase of learning manual wheelchair propulsion
.
Am J Phys Med Rehabil
. 2003;82:504–510
.
MEDLINE |
CrossRef
27.
27
Sabick MB
, Kotajarvi BR
, An KN
.
A new method to quantify demand on the upper extremity during manual wheelchair propulsion
.
Arch Phys Med Rehabil
. 2004;85:1151–1159
.
Abstract | Full Text |
Full-Text PDF (319 KB)
|
CrossRef
28.
28
Wu H
, Berglund L
, Su F
, et al.
An instrumented wheel for kinetic analysis of wheelchair propulsion
.
J Biomech Eng
. 1998;120:533–535
.
MEDLINE |
CrossRef
29.
29
Boninger ML
, Cooper RA
, Baldwin MA
, Shimada SD
, Koontz A
.
Wheelchair pushrim kinetics
(body weight and median nerve function)
.
Arch Phys Med Rehabil
. 1999;80:910–915
.
Abstract |
Full-Text PDF (1232 KB)
|
CrossRef
30.
30
Boninger ML
, Baldwin M
, Cooper RA
, Koontz A
, Chan L
.
Manual wheelchair pushrim biomechanics and axle position
.
Arch Phys Med Rehabil
. 2000;81:608–613
.
Abstract | Full Text |
Full-Text PDF (180 KB)
|
CrossRef
31.
31
de Groot S
, Veeger HE
, Hollander AP
, van der Woude LH
.
Influence of task complexity on mechanical efficiency and propulsion technique during learning of hand rim wheelchair propulsion
.
Med Eng Physics
. 2005;27:41–49
.
32.
32
van der Linden ML
, Valent L
, Veeger HE
, van der Woude LH
.
The effect of wheelchair handrim tube diameter on propulsion efficiency and force application (tube diameter and efficiency in wheelchairs)
.
IEEE Trans Rehabil Eng
. 1996;4:123–132
.
MEDLINE |
CrossRef
33.
33
van der Woude LH
, Veeger HE
, Dallmeijer AJ
, Janssen TW
, Rozendaal LA
.
Biomechanics and physiology in active manual wheelchair propulsion
.
Med Eng Physics
. 2001;23:713–733
.
a Orthopedic Biomechanics Lab, Mayo Clinic, Rochester, MN b Department of Physical Medicine and Rehabilitation, Mayo Clinic, Rochester, MN  Reprint requests to Kai-Nan An, PhD, Orthopedic Biomechanics Lab, Guggenheim 128, Mayo Clinic, Rochester, MN 55905.
Supported by the Jacob and Valeria Langeloth Foundation. No commercial party having a direct financial interest in the results of the research supporting this article has or will confer a benefit upon the authors or upon any organization with which the authors are associated. PII: S0003-9993(05)01532-7 doi:10.1016/j.apmr.2005.12.033 © 2006 American Congress of Rehabilitation Medicine and the American Academy of Physical Medicine and Rehabilitation. Published by Elsevier Inc. All rights reserved. | |
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