Technology and Health Care 22 (2014) 805–815 DOI 10.3233/THC-140856 IOS Press
805
Measuring gait pattern in elderly individuals by using a plantar pressure measurement device Kanako Nakajimaa,∗, Emi Anzaia , Yumi Iwakamib , Shuichi Inoc , Kazuhiko Yamashitab,d and Yuji Ohtaa a Department
of Human Life and Environmental Sciences, Graduate School of Humanities and Science, Ochanomizu University, Tokyo, Japan b Faculty of Healthcare, Division of Healthcare Informatics, Tokyo Healthcare University, Tokyo, Japan c Institute for Human Science and Biomedical Engineering, National Institute of Advanced Industrial Science and Technology, Ibaraki, Japan d Division of Health Sciences, Graduate School of Medicine, Osaka University, Osaka, Japan Received 24 June 2014 Accepted 20 July 2014 Abstract. BACKGROUND: Hip fracture in the elderly is a serious problem, and solutions to prevent falls are needed. OBJECTIVE: This study focused on elucidating data critical to fall prevention by evaluating ambulatory function, and we achieved this by developing a plantar pressure measurement device to determine gait function. METHODS: Our device enables measurement of gait function in the unrestrained state by transmitting wireless data. In this study, we applied the device to field experiments involving 98 subjects (39 healthy individuals, 44 elderly non-fallers, and 15 elderly fallers). Gait features were determined by measuring the pressure values and foot contact patterns used as gait function parameters in previous studies. RESULTS: In particular, decreased peak pressure values were noted at heel strike and toe off during walking in elderly fallers compared with elderly non-fallers. In addition, compared with healthy subjects, elderly fallers also showed extension of the double support phase, and differences in individual gait pattern features were observed between the groups. CONCLUSIONS: Experiments confirmed that our device can be used to obtain the gait features of a diverse group of elderly individuals. Moreover, our device enables objective and quantitative evaluation of gait function and thus may be useful for evaluating gait function in the elderly. Keywords: Elderly, plantar pressure, gait feature, wireless monitoring
1. Introduction Hip fracture can result in elderly individuals becoming bedridden. Bone fractures from falls not only decrease quality of life, but also are a burden on medical expenses. One-third of the elderly population ∗ Corresponding author: Kanako Nakajima, Ochanomizu University, 2-1-1, Otsuka, Bunkyo-ku, Tokyo 112-8610, Japan. Tel.: +81 3 5978 5740; Fax: +81 3 5978 5899; E-mail: [email protected].
c 2014 – IOS Press and the authors. All rights reserved 0928-7329/14/$27.50
806 K. Nakajima et al. / Measuring gait pattern in elderly individuals by using a plantar pressure measurement device
experience a fall at least once a year, and the prevalence of multiple annual falls in this population is about 15% [1–3]. Fracture from falls occurs at a frequency of 5–10% in accidents [4–6], and 13% of elderly deaths are due to falls [7]. It is, therefore, necessary to establish effective fall prevention measures given the increase in the elderly population. According to the guidelines for the prevention of fall in older persons of the American Geriatrics Society and the British Geriatrics Society, fall factors include age (> 80 years), sex (female), impaired migration, history of falls, physical function, and the use of medications [8]. Of all the factors, however, decreased lower-limb muscle strength carries the highest risk for falls, followed in order by past history of falls, gait disorder, and balance disabilities [8, 9]. Studies on the physical functions of elderly people [10–16] have included subjective evaluations based on questionnaires and quantitative methods involving equipment such as force plates, stabilographs, and three-dimensional motion systems [12–16]. However, these methods are not practical for assessing the majority of community-dwelling elderly people and therefore cannot be used to determine the risks of fall with the aim of developing fall prevention measures. Furthermore, these devices are usually large, heavy, and expensive. Consequently, they are not widely used in the health and welfare fields associated with the elderly. There is thus a need for simple and quantitative methods and evaluation techniques that can be utilized in the field to assess the risks of falls in the elderly. This study focuses on quantitative evaluation of gait function by means of a custom-built plantar pressure measurement device. In previous study, Saito et al. reported that a reproducibility experiment and a comparison experiment for validation of our device using F-scan system were conducted [17]. Anzai et al. indicated that our device has strongly correlated with a stationary type stabilometer in measurement of Center of Pressure (CoP) [18]. This paper discusses the ambulatory functions of many elderly people by using our device in field experiments. 2. Device design Figure 1(a) shows the device attached to a pair of shoes. Seven pressure-sensitive electric rubber sensors (PSCR sensor, Yokohama Image System Co., Ltd., Japan, 15 × 10 × 0.8 mm; length × height × thickness) (Fig. 1(b)), which measure changes in conductivity (resistance values) in response to external force, were placed on the insole of each shoe. When stress is applied to the pressure-sensing portion of the sensor, the pressure-sensitive rubber changes the magnitude of resistance according to its change in shape. The sensor responds to stimuli in the range of 25–500 kPa. Figure 1(c) shows the sensor arrangement in the shoe insole. Sensors were placed at (1) heel, (2) lateral midfoot, (3) lateral forefoot, (4) great toe, (5) head of first metatarsal, (6) center midfoot, and (7) center forefoot. These locations were chosen to anatomically characterize changes in foot pressure during standing and during walking. The sensors are attached to a wireless unit, which transmits the obtained data to a control PC, thus enabling plantar pressure measurement with subjects in an unconstrained state. Wireless transmission is via Bluetooth with a sampling frequency of 100 Hz and has a maximum range of about 50 m. The power source (lithium battery, 3V, 400 mAh) had a life of approximately 8 hour during continuous operation. The software application to receive the sensor data was developed in Microsoft Visual C#. The device was designed to fit shoes of different sizes, and its combined mass (sensors, transmitter, and battery) was 257 grams per foot. Some sensors and insoles in each size were prepared (22.0 cm, 23.0 cm, 24.0 cm, and 25.0 cm). All sensors were calibrated before tests. Examples of output data (pressure values of the right foot during a single step during walking) are shown in Fig. 1(d). These data make it possible to quantitatively observe walking motion by measuring
K. Nakajima et al. / Measuring gait pattern in elderly individuals by using a plantar pressure measurement device 807 10 mm 15mm
(a) Plantar pressure measurement
(b) Pressure-sensitive electric
device attached to a pair of shoes
rubber sensor (PSCR sensor)
(c) Sensor locations
Toe off
Heel contact
350 Ch7
Pressure [kPa]
300
Ch6
250
Ch5
200
Ch4 Ch3
150
④ ⑤⑦ ③ ⑥
②
Ch2 100
Ch1
①
50
Time [s]
0 0
0.2
0.4
0.6
0.8
(d) Examples of plantar pressure values of each sensor during walking
Fig. 1. Plantar pressure measurement device. (a) Plantar pressure measurement device attached to a pair of shoes. (b) Pressure-sensitive electric rubber sensor (PSCR sensor). (c) Sensor locations: (1) heel, (2) lateral midfoot, (3) lateral forefoot, (4) great toe, (5) head of first metatarsal, (6) center midfoot, and (7) center forefoot. (d) Examples of plantar pressure values of each sensor during walking.
pressure changes on different parts of the foot. The waveforms of Ch1 (heel) and Ch4 (toe area) show clear bimodal pressure peaks representing heel contact and toe off.
3. Methods 3.1. Subjects Measurement of plantar pressure during walking was conducted in 98 subjects (Table 1); 39 healthy (mean age, 59.8 ± 6.3 years) and 59 community-dwelling elderly (mean age, 74.6 ± 4.9 years) subjects. The purpose of this experiment was to elucidate the differences in walking patterns by age and history of falls. All subjects could walk on their own without a stick and were classified into three groups by age and annual history of falls in the past year (healthy, elderly non-fallers, and elderly fallers). Fall history was investigated using a questionnaire. Fifteen elderly subjects in 59 elderly people experienced at least
808 K. Nakajima et al. / Measuring gait pattern in elderly individuals by using a plantar pressure measurement device Table 1 Subject characteristics
Table 2 Information of elderly fallers
one fall within the last 12 months, but they didn’t have history of fracture from falls. There were no people who have experiences of orthopedic surgery from falls (e.g. by hip replacement) in all subjects. Detailed information of elderly fallers from a questionnaire was indicated in Table 2. 3.2. Experimental protocol Subjects attached the device and walked 10 m at their own speed. The content and purpose of this study were explained to the subjects and all provided consent to participate. This study was carried out with the approval of the Ethics Committee of Ochanomizu University (Tokyo, Japan). Sufficient numbers of staff were on hand to minimize the risk of falls or accidents during the experiment. 3.3. Data analysis This study focuses on plantar pressure values and contact patterns during walking. In clinical practice, the plantar pressure is used as the observation of ambulatory function and the evaluation of diabetic foot abnormality [19–21]. The beginning and end phase during walking are unstable in human gait. Thus, gait analysis excluded the data of the first and final four steps. As pressure values are influenced by the subject’s body weight and walking speeds, data were normalized by dividing the pressure values by these parameters. The gait speed was calculated from the gait data.
K. Nakajima et al. / Measuring gait pattern in elderly individuals by using a plantar pressure measurement device 809
Sensor number
Left foot 7 6 5 4 3 2 1 0
Right foot
13.6%
100%
0% 0
79.7% 20
40
60
80
100
[B] 20.3% 13.6 + 20.3 = 33.9%
[A] 13.6%
Duration of double support phase [%] Fig. 2. The calculation method of double support phase. 500
Ch7
Ch7
Ch6
400
Pressure [kPa]
Pressure [kPa]
500
Ch5
300
Ch4
200
Ch3 Ch2
100 0 0
0.2
0.4
0.6
Ch1 Time [s] 0.8
400
Ch6 Ch5
300
Ch4
200
Ch3 Ch2
100
Ch1 Time [s]
0
0
(a) Healthy subject
0.4
0.6
0.8
(b) Elderly non-faller
500
Pressure [kPa]
0.2
Ch7 Ch6 Ch5 Ch4 Ch3 Ch2 Ch1
400 300 200 100 0 0
0.2
0.4
0.6
Time [s] 0.8
(c) Elderly faller Fig. 3. Examples of pressure changes in one subject from each group.
In analysis of contact patterns during walking, the calculation method is shown in Fig. 2. The time from the beginning of the stance phase to the end point was expressed as 100% by adding the ratio of the time of [A] and [B], where [A] is the phase between the start of the stance phase and the end of the output values of the opposite leg and [B] is the phase between the touch down of the opposite leg and the end point of the stance phase. Analysis of variance with Bonferroni’s test for multiple comparisons was performed to analyze the physical functions and the effect of age on the characteristics of plantar pressure and foot contact patterns. Statistical analysis was performed using SPSS Version 20.0.0 statistical analysis software (IBM Japan, Tokyo, Japan).
Pressure [kPa]/Body weight [kg]/Gait speed [m/s]
810 K. Nakajima et al. / Measuring gait pattern in elderly individuals by using a plantar pressure measurement device
10
* *
* *
9
Healthy subjects *
Elderly non-fallers
8
Elderly fallers
7
④ ③⑦⑤
6 5 * *
4
⑥ ② *P
805
Measuring gait pattern in elderly individuals by using a plantar pressure measurement device Kanako Nakajimaa,∗, Emi Anzaia , Yumi Iwakamib , Shuichi Inoc , Kazuhiko Yamashitab,d and Yuji Ohtaa a Department
of Human Life and Environmental Sciences, Graduate School of Humanities and Science, Ochanomizu University, Tokyo, Japan b Faculty of Healthcare, Division of Healthcare Informatics, Tokyo Healthcare University, Tokyo, Japan c Institute for Human Science and Biomedical Engineering, National Institute of Advanced Industrial Science and Technology, Ibaraki, Japan d Division of Health Sciences, Graduate School of Medicine, Osaka University, Osaka, Japan Received 24 June 2014 Accepted 20 July 2014 Abstract. BACKGROUND: Hip fracture in the elderly is a serious problem, and solutions to prevent falls are needed. OBJECTIVE: This study focused on elucidating data critical to fall prevention by evaluating ambulatory function, and we achieved this by developing a plantar pressure measurement device to determine gait function. METHODS: Our device enables measurement of gait function in the unrestrained state by transmitting wireless data. In this study, we applied the device to field experiments involving 98 subjects (39 healthy individuals, 44 elderly non-fallers, and 15 elderly fallers). Gait features were determined by measuring the pressure values and foot contact patterns used as gait function parameters in previous studies. RESULTS: In particular, decreased peak pressure values were noted at heel strike and toe off during walking in elderly fallers compared with elderly non-fallers. In addition, compared with healthy subjects, elderly fallers also showed extension of the double support phase, and differences in individual gait pattern features were observed between the groups. CONCLUSIONS: Experiments confirmed that our device can be used to obtain the gait features of a diverse group of elderly individuals. Moreover, our device enables objective and quantitative evaluation of gait function and thus may be useful for evaluating gait function in the elderly. Keywords: Elderly, plantar pressure, gait feature, wireless monitoring
1. Introduction Hip fracture can result in elderly individuals becoming bedridden. Bone fractures from falls not only decrease quality of life, but also are a burden on medical expenses. One-third of the elderly population ∗ Corresponding author: Kanako Nakajima, Ochanomizu University, 2-1-1, Otsuka, Bunkyo-ku, Tokyo 112-8610, Japan. Tel.: +81 3 5978 5740; Fax: +81 3 5978 5899; E-mail: [email protected].
c 2014 – IOS Press and the authors. All rights reserved 0928-7329/14/$27.50
806 K. Nakajima et al. / Measuring gait pattern in elderly individuals by using a plantar pressure measurement device
experience a fall at least once a year, and the prevalence of multiple annual falls in this population is about 15% [1–3]. Fracture from falls occurs at a frequency of 5–10% in accidents [4–6], and 13% of elderly deaths are due to falls [7]. It is, therefore, necessary to establish effective fall prevention measures given the increase in the elderly population. According to the guidelines for the prevention of fall in older persons of the American Geriatrics Society and the British Geriatrics Society, fall factors include age (> 80 years), sex (female), impaired migration, history of falls, physical function, and the use of medications [8]. Of all the factors, however, decreased lower-limb muscle strength carries the highest risk for falls, followed in order by past history of falls, gait disorder, and balance disabilities [8, 9]. Studies on the physical functions of elderly people [10–16] have included subjective evaluations based on questionnaires and quantitative methods involving equipment such as force plates, stabilographs, and three-dimensional motion systems [12–16]. However, these methods are not practical for assessing the majority of community-dwelling elderly people and therefore cannot be used to determine the risks of fall with the aim of developing fall prevention measures. Furthermore, these devices are usually large, heavy, and expensive. Consequently, they are not widely used in the health and welfare fields associated with the elderly. There is thus a need for simple and quantitative methods and evaluation techniques that can be utilized in the field to assess the risks of falls in the elderly. This study focuses on quantitative evaluation of gait function by means of a custom-built plantar pressure measurement device. In previous study, Saito et al. reported that a reproducibility experiment and a comparison experiment for validation of our device using F-scan system were conducted [17]. Anzai et al. indicated that our device has strongly correlated with a stationary type stabilometer in measurement of Center of Pressure (CoP) [18]. This paper discusses the ambulatory functions of many elderly people by using our device in field experiments. 2. Device design Figure 1(a) shows the device attached to a pair of shoes. Seven pressure-sensitive electric rubber sensors (PSCR sensor, Yokohama Image System Co., Ltd., Japan, 15 × 10 × 0.8 mm; length × height × thickness) (Fig. 1(b)), which measure changes in conductivity (resistance values) in response to external force, were placed on the insole of each shoe. When stress is applied to the pressure-sensing portion of the sensor, the pressure-sensitive rubber changes the magnitude of resistance according to its change in shape. The sensor responds to stimuli in the range of 25–500 kPa. Figure 1(c) shows the sensor arrangement in the shoe insole. Sensors were placed at (1) heel, (2) lateral midfoot, (3) lateral forefoot, (4) great toe, (5) head of first metatarsal, (6) center midfoot, and (7) center forefoot. These locations were chosen to anatomically characterize changes in foot pressure during standing and during walking. The sensors are attached to a wireless unit, which transmits the obtained data to a control PC, thus enabling plantar pressure measurement with subjects in an unconstrained state. Wireless transmission is via Bluetooth with a sampling frequency of 100 Hz and has a maximum range of about 50 m. The power source (lithium battery, 3V, 400 mAh) had a life of approximately 8 hour during continuous operation. The software application to receive the sensor data was developed in Microsoft Visual C#. The device was designed to fit shoes of different sizes, and its combined mass (sensors, transmitter, and battery) was 257 grams per foot. Some sensors and insoles in each size were prepared (22.0 cm, 23.0 cm, 24.0 cm, and 25.0 cm). All sensors were calibrated before tests. Examples of output data (pressure values of the right foot during a single step during walking) are shown in Fig. 1(d). These data make it possible to quantitatively observe walking motion by measuring
K. Nakajima et al. / Measuring gait pattern in elderly individuals by using a plantar pressure measurement device 807 10 mm 15mm
(a) Plantar pressure measurement
(b) Pressure-sensitive electric
device attached to a pair of shoes
rubber sensor (PSCR sensor)
(c) Sensor locations
Toe off
Heel contact
350 Ch7
Pressure [kPa]
300
Ch6
250
Ch5
200
Ch4 Ch3
150
④ ⑤⑦ ③ ⑥
②
Ch2 100
Ch1
①
50
Time [s]
0 0
0.2
0.4
0.6
0.8
(d) Examples of plantar pressure values of each sensor during walking
Fig. 1. Plantar pressure measurement device. (a) Plantar pressure measurement device attached to a pair of shoes. (b) Pressure-sensitive electric rubber sensor (PSCR sensor). (c) Sensor locations: (1) heel, (2) lateral midfoot, (3) lateral forefoot, (4) great toe, (5) head of first metatarsal, (6) center midfoot, and (7) center forefoot. (d) Examples of plantar pressure values of each sensor during walking.
pressure changes on different parts of the foot. The waveforms of Ch1 (heel) and Ch4 (toe area) show clear bimodal pressure peaks representing heel contact and toe off.
3. Methods 3.1. Subjects Measurement of plantar pressure during walking was conducted in 98 subjects (Table 1); 39 healthy (mean age, 59.8 ± 6.3 years) and 59 community-dwelling elderly (mean age, 74.6 ± 4.9 years) subjects. The purpose of this experiment was to elucidate the differences in walking patterns by age and history of falls. All subjects could walk on their own without a stick and were classified into three groups by age and annual history of falls in the past year (healthy, elderly non-fallers, and elderly fallers). Fall history was investigated using a questionnaire. Fifteen elderly subjects in 59 elderly people experienced at least
808 K. Nakajima et al. / Measuring gait pattern in elderly individuals by using a plantar pressure measurement device Table 1 Subject characteristics
Table 2 Information of elderly fallers
one fall within the last 12 months, but they didn’t have history of fracture from falls. There were no people who have experiences of orthopedic surgery from falls (e.g. by hip replacement) in all subjects. Detailed information of elderly fallers from a questionnaire was indicated in Table 2. 3.2. Experimental protocol Subjects attached the device and walked 10 m at their own speed. The content and purpose of this study were explained to the subjects and all provided consent to participate. This study was carried out with the approval of the Ethics Committee of Ochanomizu University (Tokyo, Japan). Sufficient numbers of staff were on hand to minimize the risk of falls or accidents during the experiment. 3.3. Data analysis This study focuses on plantar pressure values and contact patterns during walking. In clinical practice, the plantar pressure is used as the observation of ambulatory function and the evaluation of diabetic foot abnormality [19–21]. The beginning and end phase during walking are unstable in human gait. Thus, gait analysis excluded the data of the first and final four steps. As pressure values are influenced by the subject’s body weight and walking speeds, data were normalized by dividing the pressure values by these parameters. The gait speed was calculated from the gait data.
K. Nakajima et al. / Measuring gait pattern in elderly individuals by using a plantar pressure measurement device 809
Sensor number
Left foot 7 6 5 4 3 2 1 0
Right foot
13.6%
100%
0% 0
79.7% 20
40
60
80
100
[B] 20.3% 13.6 + 20.3 = 33.9%
[A] 13.6%
Duration of double support phase [%] Fig. 2. The calculation method of double support phase. 500
Ch7
Ch7
Ch6
400
Pressure [kPa]
Pressure [kPa]
500
Ch5
300
Ch4
200
Ch3 Ch2
100 0 0
0.2
0.4
0.6
Ch1 Time [s] 0.8
400
Ch6 Ch5
300
Ch4
200
Ch3 Ch2
100
Ch1 Time [s]
0
0
(a) Healthy subject
0.4
0.6
0.8
(b) Elderly non-faller
500
Pressure [kPa]
0.2
Ch7 Ch6 Ch5 Ch4 Ch3 Ch2 Ch1
400 300 200 100 0 0
0.2
0.4
0.6
Time [s] 0.8
(c) Elderly faller Fig. 3. Examples of pressure changes in one subject from each group.
In analysis of contact patterns during walking, the calculation method is shown in Fig. 2. The time from the beginning of the stance phase to the end point was expressed as 100% by adding the ratio of the time of [A] and [B], where [A] is the phase between the start of the stance phase and the end of the output values of the opposite leg and [B] is the phase between the touch down of the opposite leg and the end point of the stance phase. Analysis of variance with Bonferroni’s test for multiple comparisons was performed to analyze the physical functions and the effect of age on the characteristics of plantar pressure and foot contact patterns. Statistical analysis was performed using SPSS Version 20.0.0 statistical analysis software (IBM Japan, Tokyo, Japan).
Pressure [kPa]/Body weight [kg]/Gait speed [m/s]
810 K. Nakajima et al. / Measuring gait pattern in elderly individuals by using a plantar pressure measurement device
10
* *
* *
9
Healthy subjects *
Elderly non-fallers
8
Elderly fallers
7
④ ③⑦⑤
6 5 * *
4
⑥ ② *P
