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Special Issue "Wearable Gait Sensors"

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: closed (15 November 2013)

Special Issue Editor

Guest Editor
Prof. Dr. Shigeru Tadano

Division of Human Mechanical Systems and Design, Faculty of Engineering, Hokkaido University, Kita-ku, Kita 13, Nishi 8, Sapporo, 060-8628, Japan
E-Mail
Fax: +81 11 706 6405
Interests: bio-mechanical engineering; musculo-skeletal and orthopaedic biomechanics; bone mechanics; medical and healthcare engineering; universal design for aged persons

Special Issue Information

Dear Colleagues,

The availability of multifunctional sensors in combination with small, high capacity power sources in recent years have made it possible for the development of wearable sensor systems. Wearable sensors are small electronic devices placed on the human body to measure various kinds of Data such as acceleration, angular velocity, magnetic fields, EMG, sound etc. Due to their low-cost and convenient manner for measuring data, wearable sensor systems have been attracting attention as a diagnostic or monitoring tool for gait. Wearable gait sensors have the advantage of being able to measure gait for long periods of time and taking measurements outside the clinical office, such as inside the home for health monitoring during daily activities. This will be useful for populations facing an ageing society. Wearable gait sensors may provide information of changes in the body of related to aging, thus making it possible for early diagnosis of patients by clinicians. Though much work has been reported using wearable sensors for gait analysis and health monitoring, the interpretation of the collected data is difficult and this field of research is still a work in progress.

This special issue will address recent technological advancements on wearable sensors intended for gait related applications. We invite review articles and original research papers aimed at proposing new kinds of wearable gait sensor systems, new methods for sensor signal processing, reports on its clinical applications such as health monitoring, rehabilitation and gait analysis.

Prof. Dr. Shigeru Tadano
Guest Editor

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Keywords

  • wearable sensor systems
  • gait analysis
  • diagnostic tool
  • health monitoring
  • daily activity
  • aged motion

Published Papers (31 papers)

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Open AccessArticle Clinical Evaluation of a Mobile Sensor-Based Gait Analysis Method for Outcome Measurement after Knee Arthroplasty
Sensors 2014, 14(9), 15953-15964; doi:10.3390/s140915953
Received: 16 November 2013 / Revised: 28 July 2014 / Accepted: 22 August 2014 / Published: 28 August 2014
Cited by 5 | PDF Full-text (997 KB) | HTML Full-text | XML Full-text
Abstract
Clinical scores and motion-capturing gait analysis are today’s gold standard for outcome measurement after knee arthroplasty, although they are criticized for bias and their ability to reflect patients’ actual quality of life has been questioned. In this context, mobile gait analysis systems have
[...] Read more.
Clinical scores and motion-capturing gait analysis are today’s gold standard for outcome measurement after knee arthroplasty, although they are criticized for bias and their ability to reflect patients’ actual quality of life has been questioned. In this context, mobile gait analysis systems have been introduced to overcome some of these limitations. This study used a previously developed mobile gait analysis system comprising three inertial sensor units to evaluate daily activities and sports. The sensors were taped to the lumbosacral junction and the thigh and shank of the affected limb. The annotated raw data was evaluated using our validated proprietary software. Six patients undergoing knee arthroplasty were examined the day before and 12 months after surgery. All patients reported a satisfactory outcome, although four patients still had limitations in their desired activities. In this context, feasible running speed demonstrated a good correlation with reported impairments in sports-related activities. Notably, knee flexion angle while descending stairs and the ability to stop abruptly when running exhibited good correlation with the clinical stability and proprioception of the knee. Moreover, fatigue effects were displayed in some patients. The introduced system appears to be suitable for outcome measurement after knee arthroplasty and has the potential to overcome some of the limitations of stationary gait labs while gathering additional meaningful parameters regarding the force limits of the knee. Full article
(This article belongs to the Special Issue Wearable Gait Sensors)
Open AccessArticle IMU-Based Joint Angle Measurement for Gait Analysis
Sensors 2014, 14(4), 6891-6909; doi:10.3390/s140406891
Received: 20 November 2013 / Revised: 20 March 2014 / Accepted: 10 April 2014 / Published: 16 April 2014
Cited by 48 | PDF Full-text (2776 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
This contribution is concerned with joint angle calculation based on inertial measurement data in the context of human motion analysis. Unlike most robotic devices, the human body lacks even surfaces and right angles. Therefore, we focus on methods that avoid assuming certain orientations
[...] Read more.
This contribution is concerned with joint angle calculation based on inertial measurement data in the context of human motion analysis. Unlike most robotic devices, the human body lacks even surfaces and right angles. Therefore, we focus on methods that avoid assuming certain orientations in which the sensors are mounted with respect to the body segments. After a review of available methods that may cope with this challenge, we present a set of new methods for: (1) joint axis and position identification; and (2) flexion/extension joint angle measurement. In particular, we propose methods that use only gyroscopes and accelerometers and, therefore, do not rely on a homogeneous magnetic field. We provide results from gait trials of a transfemoral amputee in which we compare the inertial measurement unit (IMU)-based methods to an optical 3D motion capture system. Unlike most authors, we place the optical markers on anatomical landmarks instead of attaching them to the IMUs. Root mean square errors of the knee flexion/extension angles are found to be less than 1° on the prosthesis and about 3° on the human leg. For the plantar/dorsiflexion of the ankle, both deviations are about 1°. Full article
(This article belongs to the Special Issue Wearable Gait Sensors)
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Open AccessArticle Detection of Freezing of Gait in Parkinson Disease: Preliminary Results
Sensors 2014, 14(4), 6819-6827; doi:10.3390/s140406819
Received: 23 December 2013 / Revised: 9 April 2014 / Accepted: 10 April 2014 / Published: 15 April 2014
Cited by 12 | PDF Full-text (421 KB) | HTML Full-text | XML Full-text
Abstract
Freezing of gait (FOG) is a common symptom in Parkinsonism, which affects the gait pattern and is associated to a fall risk. Automatized FOG episode detection would allow systematic assessment of patient state and objective evaluation of the clinical effects of treatments. Techniques
[...] Read more.
Freezing of gait (FOG) is a common symptom in Parkinsonism, which affects the gait pattern and is associated to a fall risk. Automatized FOG episode detection would allow systematic assessment of patient state and objective evaluation of the clinical effects of treatments. Techniques have been proposed in the literature to identify FOG episodes based on the frequency properties of inertial sensor signals. Our objective here is to adapt and extend these FOG detectors in order to include other associated gait pattern changes, like festination. The proposed approach is based on a single wireless inertial sensor placed on the patient’s lower limbs. The preliminary experimental results show that existing frequency-based freezing detectors are not sufficient to detect all FOG and festination episodes and that the observation of some gait parameters such as stride length and cadence are valuable inputs to anticipate the occurrence of upcoming FOG events. Full article
(This article belongs to the Special Issue Wearable Gait Sensors)
Open AccessArticle Window Size Impact in Human Activity Recognition
Sensors 2014, 14(4), 6474-6499; doi:10.3390/s140406474
Received: 10 December 2013 / Revised: 19 March 2014 / Accepted: 26 March 2014 / Published: 9 April 2014
Cited by 31 | PDF Full-text (1047 KB) | HTML Full-text | XML Full-text
Abstract
Signal segmentation is a crucial stage in the activity recognition process; however, this has been rarely and vaguely characterized so far. Windowing approaches are normally used for segmentation, but no clear consensus exists on which window size should be preferably employed. In fact,
[...] Read more.
Signal segmentation is a crucial stage in the activity recognition process; however, this has been rarely and vaguely characterized so far. Windowing approaches are normally used for segmentation, but no clear consensus exists on which window size should be preferably employed. In fact, most designs normally rely on figures used in previous works, but with no strict studies that support them. Intuitively, decreasing the window size allows for a faster activity detection, as well as reduced resources and energy needs. On the contrary, large data windows are normally considered for the recognition of complex activities. In this work, we present an extensive study to fairly characterize the windowing procedure, to determine its impact within the activity recognition process and to help clarify some of the habitual assumptions made during the recognition system design. To that end, some of the most widely used activity recognition procedures are evaluated for a wide range of window sizes and activities. From the evaluation, the interval 1–2 s proves to provide the best trade-off between recognition speed and accuracy. The study, specifically intended for on-body activity recognition systems, further provides designers with a set of guidelines devised to facilitate the system definition and configuration according to the particular application requirements and target activities. Full article
(This article belongs to the Special Issue Wearable Gait Sensors)
Open AccessArticle A Wearable System for Gait Training in Subjects with Parkinson’s Disease
Sensors 2014, 14(4), 6229-6246; doi:10.3390/s140406229
Received: 8 January 2014 / Revised: 20 March 2014 / Accepted: 24 March 2014 / Published: 28 March 2014
Cited by 14 | PDF Full-text (1541 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, a system for gait training and rehabilitation for Parkinson’s disease (PD) patients in a daily life setting is presented. It is based on a wearable architecture aimed at the provision of real-time auditory feedback. Recent studies have, in fact, shown
[...] Read more.
In this paper, a system for gait training and rehabilitation for Parkinson’s disease (PD) patients in a daily life setting is presented. It is based on a wearable architecture aimed at the provision of real-time auditory feedback. Recent studies have, in fact, shown that PD patients can receive benefit from a motor therapy based on auditory cueing and feedback, as happens in traditional rehabilitation contexts with verbal instructions given by clinical operators. To this extent, a system based on a wireless body sensor network and a smartphone has been developed. The system enables real-time extraction of gait spatio-temporal features and their comparison with a patient’s reference walking parameters captured in the lab under clinical operator supervision. Feedback is returned to the user in form of vocal messages, encouraging the user to keep her/his walking behavior or to correct it. This paper describes the overall concept, the proposed usage scenario and the parameters estimated for the gait analysis. It also presents, in detail, the hardware-software architecture of the system and the evaluation of system reliability by testing it on a few subjects. Full article
(This article belongs to the Special Issue Wearable Gait Sensors)
Open AccessArticle Use of an Activity Monitor and GPS Device to Assess Community Activity and Participation in Transtibial Amputees
Sensors 2014, 14(4), 5845-5859; doi:10.3390/s140405845
Received: 17 January 2014 / Revised: 12 March 2014 / Accepted: 15 March 2014 / Published: 25 March 2014
Cited by 3 | PDF Full-text (204 KB) | HTML Full-text | XML Full-text
Abstract
This study characterized measures of community activity and participation of transtibial amputees based on combined data from separate accelerometer and GPS devices. The relationship between community activity and participation and standard clinical measures was assessed. Forty-seven participants were recruited (78% male, mean age
[...] Read more.
This study characterized measures of community activity and participation of transtibial amputees based on combined data from separate accelerometer and GPS devices. The relationship between community activity and participation and standard clinical measures was assessed. Forty-seven participants were recruited (78% male, mean age 60.5 years). Participants wore the accelerometer and GPS devices for seven consecutive days. Data were linked to assess community activity (community based step counts) and community participation (number of community visits). Community activity and participation were compared across amputee K-level groups. Forty-six participants completed the study. On average each participant completed 16,645 (standard deviation (SD) 13,274) community steps and 16 (SD 10.9) community visits over seven days. There were differences between K-level groups for measures of community activity (F(2,45) = 9.4, p < 0.001) and participation (F(2,45) = 6.9, p = 0.002) with lower functioning K1/2 amputees demonstrating lower levels of community activity and participation than K3 and K4 amputees. There was no significant difference between K3 and K4 for community activity (p = 0.28) or participation (p = 0.43). This study demonstrated methodology to link accelerometer and GPS data to assess community activity and participation in a group of transtibial amputees. Differences in K-levels do not appear to accurately reflect actual community activity or participation in higher functioning transtibial amputees. Full article
(This article belongs to the Special Issue Wearable Gait Sensors)
Open AccessArticle Gait Event Detection during Stair Walking Using a Rate Gyroscope
Sensors 2014, 14(3), 5470-5485; doi:10.3390/s140305470
Received: 29 November 2013 / Revised: 18 February 2014 / Accepted: 5 March 2014 / Published: 19 March 2014
Cited by 10 | PDF Full-text (541 KB) | HTML Full-text | XML Full-text
Abstract
Gyroscopes have been proposed as sensors for ambulatory gait analysis and functional electrical stimulation systems. These applications often require detection of the initial contact (IC) of the foot with the floor and/or final contact or foot off (FO) from the floor during outdoor
[...] Read more.
Gyroscopes have been proposed as sensors for ambulatory gait analysis and functional electrical stimulation systems. These applications often require detection of the initial contact (IC) of the foot with the floor and/or final contact or foot off (FO) from the floor during outdoor walking. Previous investigations have reported the use of a single gyroscope placed on the shank for detection of IC and FO on level ground and incline walking. This paper describes the evaluation of a gyroscope placed on the shank for determination of IC and FO in subjects ascending and descending a set of stairs. Performance was compared with a reference pressure measurement system. The absolute mean difference between the gyroscope and the reference was less than 45 ms for IC and better than 135 ms for FO for both activities. Detection success was over 93%. These results provide preliminary evidence supporting the use of a gyroscope for gait event detection when walking up and down stairs. Full article
(This article belongs to the Special Issue Wearable Gait Sensors)
Open AccessArticle Assessment of Lower Limb Prosthesis through Wearable Sensors and Thermography
Sensors 2014, 14(3), 5041-5055; doi:10.3390/s140305041
Received: 15 November 2013 / Revised: 31 January 2014 / Accepted: 7 February 2014 / Published: 11 March 2014
Cited by 3 | PDF Full-text (616 KB) | HTML Full-text | XML Full-text
Abstract
This study aimed to explore the application of infrared thermography in combination with ambulatory wearable monitoring of temperature and relative humidity, to assess the residual limb-to-liner interface in lower-limb prosthesis users. Five male traumatic transtibial amputees were involved, who reported no problems or
[...] Read more.
This study aimed to explore the application of infrared thermography in combination with ambulatory wearable monitoring of temperature and relative humidity, to assess the residual limb-to-liner interface in lower-limb prosthesis users. Five male traumatic transtibial amputees were involved, who reported no problems or discomfort while wearing the prosthesis. A thermal imaging camera was used to measure superficial thermal distribution maps of the stump. A wearable system for recording the temperature and relative humidity in up to four anatomical points was developed, tested in vitro and integrated with the measurement set. The parallel application of an infrared camera and wearable sensors provided complementary information. Four main Regions of Interest were identified on the stump (inferior patella, lateral/medial epicondyles, tibial tuberosity), with good inter-subject repeatability. An average increase of 20% in hot areas (P < 0.05) is shown after walking compared to resting conditions. The sensors inside the cuff did not provoke any discomfort during recordings and provide an inside of the thermal exchanges while walking and recording the temperature increase (a regime value is ~+1.1 ± 0.7 °C) and a more significant one (~+4.1 ± 2.3%) in humidity because of the sweat produced. This study has also begun the development of a reference data set for optimal socket/liner-stump construction. Full article
(This article belongs to the Special Issue Wearable Gait Sensors)
Open AccessArticle Feasibility Study of a Wearable System Based on a Wireless Body Area Network for Gait Assessment in Parkinson’s Disease Patients
Sensors 2014, 14(3), 4618-4633; doi:10.3390/s140304618
Received: 15 November 2013 / Revised: 24 February 2014 / Accepted: 27 February 2014 / Published: 7 March 2014
Cited by 14 | PDF Full-text (552 KB) | HTML Full-text | XML Full-text
Abstract
Parkinson’s disease (PD) alters the motor performance of affected individuals. The dopaminergic denervation of the striatum, due to substantia nigra neuronal loss, compromises the speed, the automatism and smoothness of movements of PD patients. The development of a reliable tool for long-term monitoring
[...] Read more.
Parkinson’s disease (PD) alters the motor performance of affected individuals. The dopaminergic denervation of the striatum, due to substantia nigra neuronal loss, compromises the speed, the automatism and smoothness of movements of PD patients. The development of a reliable tool for long-term monitoring of PD symptoms would allow the accurate assessment of the clinical status during the different PD stages and the evaluation of motor complications. Furthermore, it would be very useful both for routine clinical care as well as for testing novel therapies. Within this context we have validated the feasibility of using a Body Network Area (BAN) of wireless accelerometers to perform continuous at home gait monitoring of PD patients. The analysis addresses the assessment of the system performance working in real environments. Full article
(This article belongs to the Special Issue Wearable Gait Sensors)
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Open AccessArticle A Fuzzy Controller for Lower Limb Exoskeletons during Sit-to-Stand and Stand-to-Sit Movement Using Wearable Sensors
Sensors 2014, 14(3), 4342-4363; doi:10.3390/s140304342
Received: 18 November 2013 / Revised: 29 January 2014 / Accepted: 7 February 2014 / Published: 4 March 2014
Cited by 6 | PDF Full-text (1472 KB) | HTML Full-text | XML Full-text
Abstract
Human motion is a daily and rhythmic activity. The exoskeleton concept is a very positive scientific approach for human rehabilitation in case of lower limb impairment. Although the exoskeleton shows potential, it is not yet applied extensively in clinical rehabilitation. In this research,
[...] Read more.
Human motion is a daily and rhythmic activity. The exoskeleton concept is a very positive scientific approach for human rehabilitation in case of lower limb impairment. Although the exoskeleton shows potential, it is not yet applied extensively in clinical rehabilitation. In this research, a fuzzy based control algorithm is proposed for lower limb exoskeletons during sit-to-stand and stand-to-sit movements. Surface electromyograms (EMGs) are acquired from the vastus lateralis muscle using a wearable EMG sensor. The resultant acceleration angle along the z-axis is determined from a kinematics sensor. Twenty volunteers were chosen to perform the experiments. The whole experiment was accomplished in two phases. In the first phase, acceleration angles and EMG data were acquired from the volunteers during both sit-to-stand and stand-to-sit motions. During sit-to-stand movements, the average acceleration angle at activation was 11°–48° and the EMG varied from −0.19 mV to +0.19 mV. On the other hand, during stand-to-sit movements, the average acceleration angle was found to be 57.5°–108° at the activation point and the EMG varied from −0.32 mV to +0.32 mV. In the second phase, a fuzzy controller was designed from the experimental data. The controller was tested and validated with both offline and real time data using LabVIEW. Full article
(This article belongs to the Special Issue Wearable Gait Sensors)
Open AccessArticle A Textile-Based Wearable Sensing Device Designed for Monitoring the Flexion Angle of Elbow and Knee Movements
Sensors 2014, 14(3), 4050-4059; doi:10.3390/s140304050
Received: 25 December 2013 / Revised: 17 February 2014 / Accepted: 17 February 2014 / Published: 26 February 2014
Cited by 8 | PDF Full-text (564 KB) | HTML Full-text | XML Full-text
Abstract
In this work a wearable gesture sensing device consisting of a textile strain sensor, using elastic conductive webbing, was designed for monitoring the flexion angle of elbow and knee movements. The elastic conductive webbing shows a linear response of resistance to the flexion
[...] Read more.
In this work a wearable gesture sensing device consisting of a textile strain sensor, using elastic conductive webbing, was designed for monitoring the flexion angle of elbow and knee movements. The elastic conductive webbing shows a linear response of resistance to the flexion angle. The wearable gesture sensing device was calibrated and then the flexion angle-resistance equation was established using an assembled gesture sensing apparatus with a variable resistor and a protractor. The proposed device successfully monitored the flexion angle during elbow and knee movements. Full article
(This article belongs to the Special Issue Wearable Gait Sensors)
Open AccessArticle Optimal Sensor Placement for Measuring Physical Activity with a 3D Accelerometer
Sensors 2014, 14(2), 3188-3206; doi:10.3390/s140203188
Received: 10 December 2013 / Revised: 24 January 2014 / Accepted: 7 February 2014 / Published: 18 February 2014
Cited by 15 | PDF Full-text (484 KB) | HTML Full-text | XML Full-text
Abstract
Accelerometer-based activity monitors are popular for monitoring physical activity. In this study, we investigated optimal sensor placement for increasing the quality of studies that utilize accelerometer data to assess physical activity. We performed a two-staged study, focused on sensor location and type of
[...] Read more.
Accelerometer-based activity monitors are popular for monitoring physical activity. In this study, we investigated optimal sensor placement for increasing the quality of studies that utilize accelerometer data to assess physical activity. We performed a two-staged study, focused on sensor location and type of mounting. Ten subjects walked at various walking speeds on a treadmill, performed a deskwork protocol, and walked on level ground, while simultaneously wearing five ProMove2 sensors with a snug fit on an elastic waist belt. We found that sensor location, type of activity, and their interaction-effect affected sensor output. The most lateral positions on the waist belt were the least sensitive for interference. The effect of mounting was explored, by making two subjects repeat the experimental protocol with sensors more loosely fitted to the elastic belt. The loose fit resulted in lower sensor output, except for the deskwork protocol, where output was higher. In order to increase the reliability and to reduce the variability of sensor output, researchers should place activity sensors on the most lateral position of a participant’s waist belt. If the sensor hampers free movement, it may be positioned slightly more forward on the belt. Finally, sensors should be fitted tightly to the body. Full article
(This article belongs to the Special Issue Wearable Gait Sensors)
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Open AccessArticle Online Phase Detection Using Wearable Sensors for Walking with a Robotic Prosthesis
Sensors 2014, 14(2), 2776-2794; doi:10.3390/s140202776
Received: 19 November 2013 / Revised: 19 January 2014 / Accepted: 23 January 2014 / Published: 11 February 2014
Cited by 20 | PDF Full-text (1590 KB) | HTML Full-text | XML Full-text
Abstract
This paper presents a gait phase detection algorithm for providing feedback in walking with a robotic prosthesis. The algorithm utilizes the output signals of a wearable wireless sensory system incorporating sensorized shoe insoles and inertial measurement units attached to body segments. The principle
[...] Read more.
This paper presents a gait phase detection algorithm for providing feedback in walking with a robotic prosthesis. The algorithm utilizes the output signals of a wearable wireless sensory system incorporating sensorized shoe insoles and inertial measurement units attached to body segments. The principle of detecting transitions between gait phases is based on heuristic threshold rules, dividing a steady-state walking stride into four phases. For the evaluation of the algorithm, experiments with three amputees, walking with the robotic prosthesis and wearable sensors, were performed. Results show a high rate of successful detection for all four phases (the average success rate across all subjects >90%). A comparison of the proposed method to an off-line trained algorithm using hidden Markov models reveals a similar performance achieved without the need for learning dataset acquisition and previous model training. Full article
(This article belongs to the Special Issue Wearable Gait Sensors)
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Open AccessArticle Wearable Monitoring Devices for Assistive Technology: Case Studies in Post-Polio Syndrome
Sensors 2014, 14(2), 2012-2027; doi:10.3390/s140202012
Received: 17 October 2013 / Revised: 16 January 2014 / Accepted: 17 January 2014 / Published: 24 January 2014
Cited by 4 | PDF Full-text (631 KB) | HTML Full-text | XML Full-text
Abstract
The correct choice and customization of an orthosis are crucial to obtain the best comfort and efficiency. This study explored the feasibility of a multivariate quantitative assessment of the functional efficiency of lower limb orthosis through a novel wearable system. Gait basographic parameters
[...] Read more.
The correct choice and customization of an orthosis are crucial to obtain the best comfort and efficiency. This study explored the feasibility of a multivariate quantitative assessment of the functional efficiency of lower limb orthosis through a novel wearable system. Gait basographic parameters and energetic indexes were analysed during a Six-Minute Walking Test (6-MWT) through a cost-effective, non-invasive polygraph device, with a multichannel wireless transmission, that carried out electro-cardiograph (ECG); impedance-cardiograph (ICG); and lower-limb accelerations detection. Four subjects affected by Post-Polio Syndrome (PPS) were recruited. The wearable device and the semi-automatic post-processing software provided a novel set of objective data to assess the overall efficiency of the patient-orthosis system. Despite the small number of examined subjects, the results obtained with this new approach encourage the application of the method thus enlarging the dataset to validate this promising protocol and measuring system in supporting clinical decisions and out of a laboratory environment. Full article
(This article belongs to the Special Issue Wearable Gait Sensors)
Open AccessArticle Markov Jump Linear Systems-Based Position Estimation for Lower Limb Exoskeletons
Sensors 2014, 14(1), 1835-1849; doi:10.3390/s140101835
Received: 10 December 2013 / Revised: 16 January 2014 / Accepted: 17 January 2014 / Published: 22 January 2014
Cited by 5 | PDF Full-text (1531 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, we deal with Markov Jump Linear Systems-based filtering applied to robotic rehabilitation. The angular positions of an impedance-controlled exoskeleton, designed to help stroke and spinal cord injured patients during walking rehabilitation, are estimated. Standard position estimate approaches adopt Kalman filters
[...] Read more.
In this paper, we deal with Markov Jump Linear Systems-based filtering applied to robotic rehabilitation. The angular positions of an impedance-controlled exoskeleton, designed to help stroke and spinal cord injured patients during walking rehabilitation, are estimated. Standard position estimate approaches adopt Kalman filters (KF) to improve the performance of inertial measurement units (IMUs) based on individual link configurations. Consequently, for a multi-body system, like a lower limb exoskeleton, the inertial measurements of one link (e.g., the shank) are not taken into account in other link position estimation (e.g., the foot). In this paper, we propose a collective modeling of all inertial sensors attached to the exoskeleton, combining them in a Markovian estimation model in order to get the best information from each sensor. In order to demonstrate the effectiveness of our approach, simulation results regarding a set of human footsteps, with four IMUs and three encoders attached to the lower limb exoskeleton, are presented. A comparative study between the Markovian estimation system and the standard one is performed considering a wide range of parametric uncertainties. Full article
(This article belongs to the Special Issue Wearable Gait Sensors)
Open AccessArticle Wearable Gait Measurement System with an Instrumented Cane for Exoskeleton Control
Sensors 2014, 14(1), 1705-1722; doi:10.3390/s140101705
Received: 15 November 2013 / Revised: 31 December 2013 / Accepted: 31 December 2013 / Published: 17 January 2014
Cited by 14 | PDF Full-text (1703 KB) | HTML Full-text | XML Full-text
Abstract
In this research we introduce a wearable sensory system for motion intention estimation and control of exoskeleton robot. The system comprises wearable inertial motion sensors and shoe-embedded force sensors. The system utilizes an instrumented cane as a part of the interface between the
[...] Read more.
In this research we introduce a wearable sensory system for motion intention estimation and control of exoskeleton robot. The system comprises wearable inertial motion sensors and shoe-embedded force sensors. The system utilizes an instrumented cane as a part of the interface between the user and the robot. The cane reflects the motion of upper limbs, and is used in terms of human inter-limb synergies. The developed control system provides assisted motion in coherence with the motion of other unassisted limbs. The system utilizes the instrumented cane together with body worn sensors, and provides assistance for start, stop and continuous walking. We verified the function of the proposed method and the developed wearable system through gait trials on treadmill and on ground. The achievement contributes to finding an intuitive and feasible interface between human and robot through wearable gait sensors for practical use of assistive technology. It also contributes to the technology for cognitively assisted locomotion, which helps the locomotion of physically challenged people. Full article
(This article belongs to the Special Issue Wearable Gait Sensors)
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Open AccessArticle Recommendations for Standardizing Validation Procedures Assessing Physical Activity of Older Persons by Monitoring Body Postures and Movements
Sensors 2014, 14(1), 1267-1277; doi:10.3390/s140101267
Received: 25 October 2013 / Revised: 26 December 2013 / Accepted: 7 January 2014 / Published: 10 January 2014
Cited by 8 | PDF Full-text (232 KB) | HTML Full-text | XML Full-text
Abstract
Physical activity is an important determinant of health and well-being in older persons and contributes to their social participation and quality of life. Hence, assessment tools are needed to study this physical activity in free-living conditions. Wearable motion sensing technology is used to
[...] Read more.
Physical activity is an important determinant of health and well-being in older persons and contributes to their social participation and quality of life. Hence, assessment tools are needed to study this physical activity in free-living conditions. Wearable motion sensing technology is used to assess physical activity. However, there is a lack of harmonisation of validation protocols and applied statistics, which make it hard to compare available and future studies. Therefore, the aim of this paper is to formulate recommendations for assessing the validity of sensor-based activity monitoring in older persons with focus on the measurement of body postures and movements. Validation studies of body-worn devices providing parameters on body postures and movements were identified and summarized and an extensive inter-active process between authors resulted in recommendations about: information on the assessed persons, the technical system, and the analysis of relevant parameters of physical activity, based on a standardized and semi-structured protocol. The recommended protocols can be regarded as a first attempt to standardize validity studies in the area of monitoring physical activity. Full article
(This article belongs to the Special Issue Wearable Gait Sensors)
Open AccessArticle A Wireless Flexible Sensorized Insole for Gait Analysis
Sensors 2014, 14(1), 1073-1093; doi:10.3390/s140101073
Received: 18 November 2013 / Revised: 30 December 2013 / Accepted: 6 January 2014 / Published: 9 January 2014
Cited by 29 | PDF Full-text (1468 KB) | HTML Full-text | XML Full-text
Abstract
This paper introduces the design and development of a novel pressure-sensitive foot insole for real-time monitoring of plantar pressure distribution during walking. The device consists of a flexible insole with 64 pressure-sensitive elements and an integrated electronic board for high-frequency data acquisition, pre-filtering,
[...] Read more.
This paper introduces the design and development of a novel pressure-sensitive foot insole for real-time monitoring of plantar pressure distribution during walking. The device consists of a flexible insole with 64 pressure-sensitive elements and an integrated electronic board for high-frequency data acquisition, pre-filtering, and wireless transmission to a remote data computing/storing unit. The pressure-sensitive technology is based on an optoelectronic technology developed at Scuola Superiore Sant’Anna. The insole is a low-cost and low-power battery-powered device. The design and development of the device is presented along with its experimental characterization and validation with healthy subjects performing a task of walking at different speeds, and benchmarked against an instrumented force platform. Full article
(This article belongs to the Special Issue Wearable Gait Sensors)
Open AccessArticle An Ambulatory Method of Identifying Anterior Cruciate Ligament Reconstructed Gait Patterns
Sensors 2014, 14(1), 887-899; doi:10.3390/s140100887
Received: 30 November 2013 / Revised: 20 December 2013 / Accepted: 26 December 2013 / Published: 7 January 2014
Cited by 10 | PDF Full-text (455 KB) | HTML Full-text | XML Full-text
Abstract
The use of inertial sensors to characterize pathological gait has traditionally been based on the calculation of temporal and spatial gait variables from inertial sensor data. This approach has proved successful in the identification of gait deviations in populations where substantial differences from
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The use of inertial sensors to characterize pathological gait has traditionally been based on the calculation of temporal and spatial gait variables from inertial sensor data. This approach has proved successful in the identification of gait deviations in populations where substantial differences from normal gait patterns exist; such as in Parkinsonian gait. However, it is not currently clear if this approach could identify more subtle gait deviations, such as those associated with musculoskeletal injury. This study investigates whether additional analysis of inertial sensor data, based on quantification of gyroscope features of interest, would provide further discriminant capability in this regard. The tested cohort consisted of a group of anterior cruciate ligament reconstructed (ACL-R) females and a group of non-injured female controls, each performed ten walking trials. Gait performance was measured simultaneously using inertial sensors and an optoelectronic marker based system. The ACL-R group displayed kinematic and kinetic deviations from the control group, but no temporal or spatial deviations. This study demonstrates that quantification of gyroscope features can successfully identify changes associated with ACL-R gait, which was not possible using spatial or temporal variables. This finding may also have a role in other clinical applications where small gait deviations exist. Full article
(This article belongs to the Special Issue Wearable Gait Sensors)
Open AccessArticle Continuous Monitoring of Turning in Patients with Movement Disability
Sensors 2014, 14(1), 356-369; doi:10.3390/s140100356
Received: 6 November 2013 / Revised: 10 December 2013 / Accepted: 11 December 2013 / Published: 27 December 2013
Cited by 19 | PDF Full-text (785 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Difficulty with turning is a major contributor to mobility disability and falls in people with movement disorders, such as Parkinson’s disease (PD). Turning often results in freezing and/or falling in patients with PD. However, asking a patient to execute a turn in the
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Difficulty with turning is a major contributor to mobility disability and falls in people with movement disorders, such as Parkinson’s disease (PD). Turning often results in freezing and/or falling in patients with PD. However, asking a patient to execute a turn in the clinic often does not reveal their impairments. Continuous monitoring of turning with wearable sensors during spontaneous daily activities may help clinicians and patients determine who is at risk of falls and could benefit from preventative interventions. In this study, we show that continuous monitoring of natural turning with wearable sensors during daily activities inside and outside the home is feasible for people with PD and elderly people. We developed an algorithm to detect and characterize turns during gait, using wearable inertial sensors. First, we validate the turning algorithm in the laboratory against a Motion Analysis system and against a video analysis of 21 PD patients and 19 control (CT) subjects wearing an inertial sensor on the pelvis. Compared to Motion Analysis and video, the algorithm maintained a sensitivity of 0.90 and 0.76 and a specificity of 0.75 and 0.65, respectively. Second, we apply the turning algorithm to data collected in the home from 12 PD and 18 CT subjects. The algorithm successfully detects turn characteristics, and the results show that, compared to controls, PD subjects tend to take shorter turns with smaller turn angles and more steps. Furthermore, PD subjects show more variability in all turn metrics throughout the day and the week. Full article
(This article belongs to the Special Issue Wearable Gait Sensors)
Open AccessArticle Integration of Human Walking Gyroscopic Data Using Empirical Mode Decomposition
Sensors 2014, 14(1), 370-381; doi:10.3390/s140100370
Received: 14 November 2013 / Revised: 18 December 2013 / Accepted: 18 December 2013 / Published: 27 December 2013
Cited by 4 | PDF Full-text (3072 KB) | HTML Full-text | XML Full-text
Abstract
The present study was aimed at evaluating the Empirical Mode Decomposition (EMD) method to estimate the 3D orientation of the lower trunk during walking using the angular velocity signals generated by a wearable inertial measurement unit (IMU) and notably flawed by drift. The
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The present study was aimed at evaluating the Empirical Mode Decomposition (EMD) method to estimate the 3D orientation of the lower trunk during walking using the angular velocity signals generated by a wearable inertial measurement unit (IMU) and notably flawed by drift. The IMU was mounted on the lower trunk (L4-L5) with its active axes aligned with the relevant anatomical axes. The proposed method performs an offline analysis, but has the advantage of not requiring any parameter tuning. The method was validated in two groups of 15 subjects, one during overground walking, with 180° turns, and the other during treadmill walking, both for steady-state and transient speeds, using stereophotogrammetric data. Comparative analysis of the results showed that the IMU/EMD method is able to successfully detrend the integrated angular velocities and estimate lateral bending, flexion-extension as well as axial rotations of the lower trunk during walking with RMS errors of 1 deg for straight walking and lower than 2.5 deg for walking with turns. Full article
(This article belongs to the Special Issue Wearable Gait Sensors)
Open AccessArticle Gait and Foot Clearance Parameters Obtained Using Shoe-Worn Inertial Sensors in a Large-Population Sample of Older Adults
Sensors 2014, 14(1), 443-457; doi:10.3390/s140100443
Received: 29 November 2013 / Revised: 17 December 2013 / Accepted: 18 December 2013 / Published: 27 December 2013
Cited by 16 | PDF Full-text (940 KB) | HTML Full-text | XML Full-text
Abstract
In order to distinguish dysfunctional gait, clinicians require a measure of reference gait parameters for each population. This study provided normative values for widely used parameters in more than 1,400 able-bodied adults over the age of 65. We also measured the foot clearance
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In order to distinguish dysfunctional gait, clinicians require a measure of reference gait parameters for each population. This study provided normative values for widely used parameters in more than 1,400 able-bodied adults over the age of 65. We also measured the foot clearance parameters (i.e., height of the foot above ground during swing phase) that are crucial to understand the complex relationship between gait and falls as well as obstacle negotiation strategies. We used a shoe-worn inertial sensor on each foot and previously validated algorithms to extract the gait parameters during 20 m walking trials in a corridor at a self-selected pace. We investigated the difference of the gait parameters between male and female participants by considering the effect of age and height factors. Besides; we examined the inter-relation of the clearance parameters with the gait speed. The sample size and breadth of gait parameters provided in this study offer a unique reference resource for the researchers. Full article
(This article belongs to the Special Issue Wearable Gait Sensors)
Open AccessArticle Detection of Illegal Race Walking: A Tool to Assist Coaching and Judging
Sensors 2013, 13(12), 16065-16074; doi:10.3390/s131216065
Received: 3 October 2013 / Revised: 5 November 2013 / Accepted: 18 November 2013 / Published: 26 November 2013
Cited by 11 | PDF Full-text (219 KB) | HTML Full-text | XML Full-text
Abstract
Current judging of race walking in international competitions relies on subjective human observation to detect illegal gait, which naturally has inherent problems. Incorrect judging decisions may devastate an athlete and possibly discredit the international governing body. The aim of this study was to
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Current judging of race walking in international competitions relies on subjective human observation to detect illegal gait, which naturally has inherent problems. Incorrect judging decisions may devastate an athlete and possibly discredit the international governing body. The aim of this study was to determine whether an inertial sensor could improve accuracy, monitor every step the athlete makes in training and/or competition. Seven nationally competitive race walkers performed a series of legal, illegal and self-selected pace races. During testing, athletes wore a single inertial sensor (100 Hz) placed at S1 of the vertebra and were simultaneously filmed using a high-speed camera (125 Hz). Of the 80 steps analyzed the high-speed camera identified 57 as illegal, the inertial sensor misidentified four of these measures (all four missed illegal steps had 0.008 s of loss of ground contact) which is considerably less than the best possible human observation of 0.06 s. Inertial sensor comparison to the camera found the typical error of estimate was 0.02 s (95% confidence limits 0.01–0.02), with a bias of 0.02 (±0.01). An inertial sensor can thus objectively improve the accuracy in detecting illegal steps (loss of ground contact) and, along with the ability to monitor every step of the athlete, could be a valuable tool to assist judges during race walk events. Full article
(This article belongs to the Special Issue Wearable Gait Sensors)
Open AccessArticle A Multifunctional Joint Angle Sensor with Measurement Adaptability
Sensors 2013, 13(11), 15274-15289; doi:10.3390/s131115274
Received: 21 August 2013 / Revised: 2 November 2013 / Accepted: 4 November 2013 / Published: 8 November 2013
PDF Full-text (964 KB) | HTML Full-text | XML Full-text
Abstract
The paper presents a multifunctional joint sensor with measurement adaptability for biological engineering applications, such as gait analysis, gesture recognition, etc. The adaptability is embodied in both static and dynamic environment measurements, both of body pose and in motion capture. Its multifunctional
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The paper presents a multifunctional joint sensor with measurement adaptability for biological engineering applications, such as gait analysis, gesture recognition, etc. The adaptability is embodied in both static and dynamic environment measurements, both of body pose and in motion capture. Its multifunctional capabilities lay in its ability of simultaneous measurement of multiple degrees of freedom (MDOF) with a single sensor to reduce system complexity. The basic working mode enables 2DOF spatial angle measurement over big ranges and stands out for its applications on different joints of different individuals without recalibration. The optional advanced working mode enables an additional DOF measurement for various applications. By employing corrugated tube as the main body, the sensor is also characterized as flexible and wearable with less restraints. MDOF variations are converted to linear displacements of the sensing elements. The simple reconstruction algorithm and small outputs volume are capable of providing real-time angles and long-term monitoring. The performance assessment of the built prototype is promising enough to indicate the feasibility of the sensor. Full article
(This article belongs to the Special Issue Wearable Gait Sensors)
Open AccessArticle Comparison of Raw Acceleration from the GENEA and ActiGraph™ GT3X+ Activity Monitors
Sensors 2013, 13(11), 14754-14763; doi:10.3390/s131114754
Received: 17 September 2013 / Revised: 21 October 2013 / Accepted: 28 October 2013 / Published: 30 October 2013
Cited by 14 | PDF Full-text (594 KB) | HTML Full-text | XML Full-text
Abstract
Purpose: To compare raw acceleration output of the ActiGraph™ GT3X+ and GENEA activity monitors. Methods: A GT3X+ and GENEA were oscillated in an orbital shaker at frequencies ranging from 0.7 to 4.0 Hz (ten 2-min trials/frequency) on a fixed radius of
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Purpose: To compare raw acceleration output of the ActiGraph™ GT3X+ and GENEA activity monitors. Methods: A GT3X+ and GENEA were oscillated in an orbital shaker at frequencies ranging from 0.7 to 4.0 Hz (ten 2-min trials/frequency) on a fixed radius of 5.08 cm. Additionally, 10 participants (age = 23.8 ± 5.4 years) wore the GT3X+ and GENEA on the dominant wrist and performed treadmill walking (2.0 and 3.5 mph) and running (5.5 and 7.5 mph) and simulated free-living activities (computer work, cleaning a room, vacuuming and throwing a ball) for 2-min each. A linear mixed model was used to compare the mean triaxial vector magnitude (VM) from the GT3X+ and GENEA at each oscillation frequency. For the human testing protocol, random forest machine-learning technique was used to develop two models using frequency domain (FD) and time domain (TD) features for each monitor. We compared activity type recognition accuracy between the GT3X+ and GENEA when the prediction model was fit using one monitor and then applied to the other. Z-statistics were used to compare the proportion of accurate predictions from the GT3X+ and GENEA for each model. Results: GENEA produced significantly higher (p < 0.05, 3.5 to 6.2%) mean VM than GT3X+ at all frequencies during shaker testing. Training the model using TD input features on the GENEA and applied to GT3X+ data yielded significantly lower (p < 0.05) prediction accuracy. Prediction accuracy was not compromised when interchangeably using FD models between monitors. Conclusions: It may be inappropriate to apply a model developed on the GENEA to predict activity type using GT3X+ data when input features are TD attributes of raw acceleration. Full article
(This article belongs to the Special Issue Wearable Gait Sensors)
Open AccessArticle Lower Limb Wearable Capacitive Sensing and Its Applications to Recognizing Human Gaits
Sensors 2013, 13(10), 13334-13355; doi:10.3390/s131013334
Received: 31 July 2013 / Revised: 10 September 2013 / Accepted: 25 September 2013 / Published: 1 October 2013
Cited by 6 | PDF Full-text (3149 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, we present an approach to sense human body capacitance and apply it to recognize lower limb locomotion modes. The proposed wearable sensing system includes sensing bands, a signal processing circuit and a gait event detection module. Experiments on long-term working
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In this paper, we present an approach to sense human body capacitance and apply it to recognize lower limb locomotion modes. The proposed wearable sensing system includes sensing bands, a signal processing circuit and a gait event detection module. Experiments on long-term working stability, adaptability to disturbance and locomotion mode recognition are carried out to validate the effectiveness of the proposed approach. Twelve able-bodied subjects are recruited, and eleven normal gait modes are investigated. With an event-dependent linear discriminant analysis classifier and feature selection procedure, four time-domain features are used for pattern recognition and satisfactory recognition accuracies (97:3% ± 0:5%, 97:0% ± 0:4%, 95:6% ± 0:9% and 97:0% ± 0:4% for four phases of one gait cycle respectively) are obtained. The accuracies are comparable with that from electromyography-based systems and inertial-based systems. The results validate the effectiveness of the proposed lower limb capacitive sensing approach in recognizing human normal gaits. Full article
(This article belongs to the Special Issue Wearable Gait Sensors)
Open AccessArticle A Telemetry System Embedded in Clothes for Indoor Localization and Elderly Health Monitoring
Sensors 2013, 13(9), 11728-11749; doi:10.3390/s130911728
Received: 14 July 2013 / Revised: 2 August 2013 / Accepted: 29 August 2013 / Published: 4 September 2013
Cited by 3 | PDF Full-text (1035 KB) | HTML Full-text | XML Full-text
Abstract
This paper presents a telemetry system used in a combined trilateration method for the precise indoor localization of the elderly who need health monitoring. The system is based on the association of two wireless technologies: ultrasonic and 802.15.4. The use of the 802.15.4
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This paper presents a telemetry system used in a combined trilateration method for the precise indoor localization of the elderly who need health monitoring. The system is based on the association of two wireless technologies: ultrasonic and 802.15.4. The use of the 802.15.4 RF signal gives the reference starting time of the ultrasonic emission (time difference of arrival method). A time of flight measurement of the ultrasonic pulses provides the distances between the mobile node and three anchor points. These distance measurements are then used to locate the mobile node using the trilateration method with an accuracy of a few centimetres. The originality of our work lies in embedding the mobile node in clothes. The system is embedded in clothes in two ways: on a shoe in order to form a “smart” shoe and in a hat in order to form a “smart” hat. Both accessories allow movements, gait speed and distance covered to be monitored for health applications. Experiments in a test room are presented to show the effectiveness of our system. Full article
(This article belongs to the Special Issue Wearable Gait Sensors)
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Open AccessArticle Measuring Accurate Body Parameters of Dressed Humans with Large-Scale Motion Using a Kinect Sensor
Sensors 2013, 13(9), 11362-11384; doi:10.3390/s130911362
Received: 7 June 2013 / Revised: 20 August 2013 / Accepted: 20 August 2013 / Published: 26 August 2013
Cited by 4 | PDF Full-text (6373 KB) | HTML Full-text | XML Full-text
Abstract
Non-contact human body measurement plays an important role in surveillance, physical healthcare, on-line business and virtual fitting. Current methods for measuring the human body without physical contact usually cannot handle humans wearing clothes, which limits their applicability in public environments. In this paper,
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Non-contact human body measurement plays an important role in surveillance, physical healthcare, on-line business and virtual fitting. Current methods for measuring the human body without physical contact usually cannot handle humans wearing clothes, which limits their applicability in public environments. In this paper, we propose an effective solution that can measure accurate parameters of the human body with large-scale motion from a Kinect sensor, assuming that the people are wearing clothes. Because motion can drive clothes attached to the human body loosely or tightly, we adopt a space-time analysis to mine the information across the posture variations. Using this information, we recover the human body, regardless of the effect of clothes, and measure the human body parameters accurately. Experimental results show that our system can perform more accurate parameter estimation on the human body than state-of-the-art methods. Full article
(This article belongs to the Special Issue Wearable Gait Sensors)
Open AccessArticle Human Body Parts Tracking and Kinematic Features Assessment Based on RSSI and Inertial Sensor Measurements
Sensors 2013, 13(9), 11289-11313; doi:10.3390/s130911289
Received: 3 July 2013 / Revised: 5 August 2013 / Accepted: 10 August 2013 / Published: 23 August 2013
Cited by 8 | PDF Full-text (648 KB) | HTML Full-text | XML Full-text
Abstract
Acquisition of patient kinematics in different environments plays an important role in the detection of risk situations such as fall detection in elderly patients, in rehabilitation of patients with injuries, and in the design of treatment plans for patients with neurological diseases. Received
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Acquisition of patient kinematics in different environments plays an important role in the detection of risk situations such as fall detection in elderly patients, in rehabilitation of patients with injuries, and in the design of treatment plans for patients with neurological diseases. Received Signal Strength Indicator (RSSI) measurements in a Body Area Network (BAN), capture the signal power on a radio link. The main aim of this paper is to demonstrate the potential of utilizing RSSI measurements in assessment of human kinematic features, and to give methods to determine these features. RSSI measurements can be used for tracking different body parts’ displacements on scales of a few centimeters, for classifying motion and gait patterns instead of inertial sensors, and to serve as an additional reference to other sensors, in particular inertial sensors. Criteria and analytical methods for body part tracking, kinematic motion feature extraction, and a Kalman filter model for aggregation of RSSI and inertial sensor were derived. The methods were verified by a set of experiments performed in an indoor environment. In the future, the use of RSSI measurements can help in continuous assessment of various kinematic features of patients during their daily life activities and enhance medical diagnosis accuracy with lower costs. Full article
(This article belongs to the Special Issue Wearable Gait Sensors)
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Open AccessArticle Three Dimensional Gait Analysis Using Wearable Acceleration and Gyro Sensors Based on Quaternion Calculations
Sensors 2013, 13(7), 9321-9343; doi:10.3390/s130709321
Received: 3 June 2013 / Revised: 11 July 2013 / Accepted: 17 July 2013 / Published: 19 July 2013
Cited by 23 | PDF Full-text (2422 KB) | HTML Full-text | XML Full-text
Abstract
This paper proposes a method for three dimensional gait analysis using wearable sensors and quaternion calculations. Seven sensor units consisting of a tri-axial acceleration and gyro sensors, were fixed to the lower limbs. The acceleration and angular velocity data of each sensor unit
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This paper proposes a method for three dimensional gait analysis using wearable sensors and quaternion calculations. Seven sensor units consisting of a tri-axial acceleration and gyro sensors, were fixed to the lower limbs. The acceleration and angular velocity data of each sensor unit were measured during level walking. The initial orientations of the sensor units were estimated using acceleration data during upright standing position and the angular displacements were estimated afterwards using angular velocity data during gait. Here, an algorithm based on quaternion calculation was implemented for orientation estimation of the sensor units. The orientations of the sensor units were converted to the orientations of the body segments by a rotation matrix obtained from a calibration trial. Body segment orientations were then used for constructing a three dimensional wire frame animation of the volunteers during the gait. Gait analysis was conducted on five volunteers, and results were compared with those from a camera-based motion analysis system. Comparisons were made for the joint trajectory in the horizontal and sagittal plane. The average RMSE and correlation coefficient (CC) were 10.14 deg and 0.98, 7.88 deg and 0.97, 9.75 deg and 0.78 for the hip, knee and ankle flexion angles, respectively. Full article
(This article belongs to the Special Issue Wearable Gait Sensors)
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Review

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Open AccessReview Gait Analysis Methods: An Overview of Wearable and Non-Wearable Systems, Highlighting Clinical Applications
Sensors 2014, 14(2), 3362-3394; doi:10.3390/s140203362
Received: 21 December 2013 / Revised: 4 February 2014 / Accepted: 10 February 2014 / Published: 19 February 2014
Cited by 46 | PDF Full-text (934 KB) | HTML Full-text | XML Full-text
Abstract
This article presents a review of the methods used in recognition and analysis of the human gait from three different approaches: image processing, floor sensors and sensors placed on the body. Progress in new technologies has led the development of a series of
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This article presents a review of the methods used in recognition and analysis of the human gait from three different approaches: image processing, floor sensors and sensors placed on the body. Progress in new technologies has led the development of a series of devices and techniques which allow for objective evaluation, making measurements more efficient and effective and providing specialists with reliable information. Firstly, an introduction of the key gait parameters and semi-subjective methods is presented. Secondly, technologies and studies on the different objective methods are reviewed. Finally, based on the latest research, the characteristics of each method are discussed. 40% of the reviewed articles published in late 2012 and 2013 were related to non-wearable systems, 37.5% presented inertial sensor-based systems, and the remaining 22.5% corresponded to other wearable systems. An increasing number of research works demonstrate that various parameters such as precision, conformability, usability or transportability have indicated that the portable systems based on body sensors are promising methods for gait analysis. Full article
(This article belongs to the Special Issue Wearable Gait Sensors)
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