The purpose of this study was to investigate the effects of walking aid on hemiplegic gait of chronic stroke patients. Twelve stroke patients participated in this study. Physiological cost index (PCI), gait speed, and climbing stairs with and without walking aid were measured and analyzed. The results showed that walking with walking aid significantly improved gait speed and reduced physiological cost index and time needed to climb stair (height 7 cm) in comparison with a walking without walking aid. In conclusion, walking aid may improve the speed and efficiency of hemiplegic gait in chronic stroke patients.

The purpose of this study was to investigate the effects of clinical characteristics of chronic stroke patients on physiological cost index (PCI) during walking. Fourteen stroke patients participated in this study. To investigate the clinical characteristics, Fugl-Meyer score (FMS), gait velocity (GV), muscle strength of the knee extensor, modified Ashworth scale (MAS) of ankle plantar flexor, devices, and gait patterns during walking were measured and analyzed. The results were as follows: Firstly, use of devices and high MAS of the ankle plantar flexor significantly increased PCI. Secondly, PCI was significantly correlated with the FMS and MAS of the ankle plantar flexor. In conclusion, inhibition of spasticity of the ankle plantar flexor is considered to reduce PCI during walking for chronic stroke patients.

Physiological Cost Index (PCI) of walking has been widely used to predict oxygen consumption in healthy subjects or patients. The purpose of this study was to evaluate the predictability of physiological cost index of walking for the amount of exercise and cardiac function. Walking exercise was conducted in 67 healthy children (age 4-12) with a self-selected comfortable walking speed on the level surface. Walking speed was calculated, and heart rate was measured before and immediately after the walking. PCI was calculated for statistical analysis. The results were as follows; 1) The walking speed tends to increase and PCI of walking tends to decrease with age. There was significant difference in walking speed and PCI of walking among three age groups (p<.05). The change of walking heart rate tends to decrease with age, however, there was no significant difference among three age groups. 2) Linear regression equation between walking speed and age was 'Y (walking speed) = 2.124X (age) + 48.286' (=.337), (p=.00). 3) The walking heart rate tends to decrease with age. Linear regression equation between walking heart rate and age was 'Y (walking heart rate) = 143.346 - 2.63X (age)' (=.3425), (p=.00). 4) The walking heart rate decreased as body surface area (BSA) increased. Linear regression equation between walking heart rate and BSA was 'Y (walking heart rate) = 149.830 - 27.115X (BSA)' (=.3066), (p=.00). In conclusion, these equations and PCI could be useful to quantify the variation of energy expenditure of children with pathological gait when compared with age-matched healthy children.

Physiological Cost Index (PCI) of walking has been widely used to predict oxygen consumption in healthy subjects or patients. The purposes of this study were to evaluate the predictability of physiological cost index of upper extremity exercise with a sander for the amount of exercise and cardiac function and to find out most efficient speed of exercise. Upper extremity exercise was conducted in 67 healthy children (age 4 -12) for 2 minutes with a sander in two different speeds, such as self selected comfortable and self selected fast speeds. Speed of sander was calculated, and heart rate were measured before and immediately after the exercise. Physiological Cost Index (PCI) of upper extremity exercise was calculated for statistical analysis. The result were as follows; 1.　Comfortable and fast speeds of the sander went up according to the increase of age, sander PCI during exercise by it, decreased as the age increased with significant difference in each group (p=0.00). The heart rate change during exercising by it, there was no significant difference. 2.　The heart rate change during the exercise by sander increased as the speed of sander increased. Linear regression equation between the heart rate change during the exercise by sander and the speed of sander were 'Y (the heart rate change by sander) = 0.332X (the speed of sander) + 12.731' (R²= 0.154). Stepwise regression showed the speed of sander affected the change of heart rate positively, and the age affected negatively (R²= 0.242, p = 0.00). 3.　The PCI during the exercise by sander decreased as the speed of sander increased. Linear regression equation between the PCI during the exercise by the sander and the speed of sander were 'Y (the PCI by sander) = -0.00495X (the speed of sander) + 2.091'(R²= 0.267), and statistic significant was recognized (p = 0.00). 4.　The speed of exercise by sander it increased as the age increased. Linear regression equation between the speed of the sander and the age were 'Y (the speed of sander) = 2.481X (the age) -0.893(R²= 0.452), and statistic significant was recognized(p = 0.00). 5.　The reliability analysis for the method of examining each PCI, showed high reliability coefficients and the value of alpha was 0.9337. In conclusion, PCI of the upper extremity exercise with a sander could be thought to predict the energy consumption from the speed of sander as there was a linear relationship between the speed of sander exercise and heart rate change with exercise. PCI of the upper extremity exercise with the self selected fast speed was most efficient. Further study with oxygen consumption analysis is recommended to apply PCI in upper extremities in patients with different pathologies in motion.

The purpose of this study was to establish modified physiological cost index (PCI) for predicting energy consumption by heart rate (HR) at isokinetic ergometer exercise testing. The subjects were twenty-eight healthy men in their twenties. All of them performed upper and lower extremity isokinetic ergometer exercise tests which had six loads (400, 500, 600, 700, 800, and 900 kg-m/min) and five loads (400, 500, 600, 700, and 800 kg-m/min) respectively. The exercise sessions were finished when HR was in plateau. HR and oxygen consumption were determined during the final minute. Resting heart rate and oxygen consumption were used for calculating heart rate, oxygen consumption changes and modified PCI. Regression analysis established the relationship between each variable to work load, HR and oxygen consumption. The results were as follows: 1) In the lower extremity ergometer exercise test, oxygen consumption increased continuously as work load increased, but in the upper extremity ergometer test, oxygen consumption only increased until work load was 700 kg-m/min. 2) HR increased as work load increased in both exercise tests, but in the upper extremity ergometer test, HR decreased from the 700 kg-m/min. 3) The modified PCI increased as work load mcreased until the 700 kg-m/min point in the lower extremity ergometer test and until the 500 kg-m/min point in the upper extremity ergometer test when it started to decrease in both tests. 4) In the lower extremity ergometer exercise test, regression analysis established the relation as = -.0215HR - .2141 where is given in l/min and HR in beat/min ( = .2677, p = .000). ln the upper extremity ergometer exercise test. regression analysis established the relation as = -.0115HR + .2746 ( = .1308, p = .000). The results of this study were similar to previous studies but were different under high work load conditions. So modified PCI should be used with only low intensity work load testing. Subjects for upper extremity ergometer exercise testing should complete a prescribed training course prior to testing, and only low intensity work load should be used for safety considerations.