|
Wednesday, 18 September 2019, 10:30 HKT/SGT | |
| | | | Source: Fujitsu Ltd | |
|
|
|
In monitoring the gait of patients, helps healthcare professionals quantify movements and record recovery processes |
KAWASAKI, Japan, Sept 18, 2019 - (JCN Newswire) - Fujitsu Laboratories Ltd. and Fujitsu Limited have developed a technology to digitize and quantify the walking patterns of patients whose movements vary due to the impact of different diseases.
| Figure: Usage of the developed algorithm
Outcome |
Medical professionals can identify the symptoms of patients by observing their way of walking. However, it is difficult to digitize symptoms as there are numerous walking characteristics that differ depending on the type and severity of the disease, and as of now, physiotherapists conduct visual inspections in most cases. Now, Fujitsu has developed a technology to automatically and accurately quantify factors such as the swing time and stance time(1) of the right and left leg as well as the difference between the movements of both legs. In the new development, feature points at the time of movement change will be determined using signal waveforms emitted from commercially available gyro sensors attached to the patients' ankles.
It is said that various symptoms such as musculoskeletal, neural and cardiovascular conditions affect the walking characteristics of patients. The new technology will enable healthcare professionals to quantify the gait of patients walking under the influence of such conditions, and as a result, they will be able to record recovery processes and help with the remote monitoring of patients, thereby improving the efficiency of medical services. Background
In the medical field, it is essential to analyze the walking of patients to examine their changing symptoms and recovery status. In fact, it is well known that symptoms such as musculoskeletal, neural and cardiovascular conditions cause walking abnormalities. Accordingly, there was a demand for a walking analysis technology that could digitally capture the same information as physiotherapists in detecting early signs of disease symptoms. Issues
A number of methods based on machine learning and rule-based algorithms have been proposed as conventional techniques for comparing and analyzing walking characteristics as quantitative data, and have attracted the attention of healthcare professionals. Nonetheless, physiotherapists work with patients diagnosed with a wide range of diseases, and the impact on their walking patterns differ significantly depending on such factors as the nature of the disease, its severity, and the location of disabled areas. Therefore, conventional techniques could not quantify various walking characteristics with high accuracy, as they could only analyze a limited number of walking patterns or were unable to prepare sufficient walking data for learning.
About the Newly Developed Technology
Fujitsu has developed a technology that can quantify the characteristics of various walking styles based on signals from gyro sensors attached to the patient's ankles. This technology makes use of the newly developed model based on the law of motion, such as the relationship between the movements of the left and right legs during walking and how different walking characteristics transition over time, detecting feature points and assigning meaning to the signal waveform emitted from the gyro sensors. In this way, the signal of the walking step alone can be clearly identified, and the feature points of the walking step, when the heel touches the ground or when the toe is off the ground, can be recognized regardless of the walking method. By measuring these feature points, walking characteristics such as stride length and swing time can be quantified with high accuracy.
Outcome
Utilizing a commercially available gyro sensor, the new technology evaluates various ways of walking, including 9 types of walking abnormalities (walking in short steps, circumduction, shuffling, etc.), enabling an accurate calculation of multiple walking characteristics. Specifically, the automatic recognition accuracy of the walking segment for walking motions was 96.5% and the extraction error of stride time (sum of stance time and swing time) was 1.8%. In other words, the new technology reduced the measurement error up to 1/3 times compared to conventional commercial products that require manual input of walking section.
Future Prospects
Fujitsu will continue to develop the new digitization technology for the utilization of walking observation data by medical professionals as well as for the remote monitoring of home patients who are rapidly increasing in number.
(1) Swing time and stance time of the left and right legs The period in which one leg does not touch the ground during one walk cycle is called swing time, and the period in which one leg stays on the ground is called stance time.
About Fujitsu Laboratories
Founded in 1968 as a wholly owned subsidiary of Fujitsu Limited, Fujitsu Laboratories Ltd. is one of the premier research centers in the world. With a global network of laboratories in Japan, China, the United States and Europe, the organization conducts a wide range of basic and applied research in the areas of Next-generation Services, Computer Servers, Networks, Electronic Devices and Advanced Materials. For more information, please see: http://www.fujitsu.com/jp/group/labs/en/.
Contact:
Fujitsu Laboratories Ltd.
Digital Innovation Core Unit
E-mail: kiduku-press2019@ml.labs.fujitsu.com
Fujitsu Limited
Public and Investor Relations
Tel: +81-3-3215-5259
URL: www.fujitsu.com/global/news/contacts/
Topic: Press release summary
Source: Fujitsu Ltd
Sectors: Electronics, Cloud & Enterprise
http://www.acnnewswire.com
From the Asia Corporate News Network
Copyright © 2024 ACN Newswire. All rights reserved. A division of Asia Corporate News Network.
|
|
|
|
|
|
Fujitsu Ltd |
Nov 19, 2024 08:02 HKT/SGT |
Supercomputer Fugaku retains first place worldwide in HPCG and Graph500 rankings |
Nov 18, 2024 11:31 HKT/SGT |
Fujitsu and SAP Fioneer enter partnership to accelerate digital transformation in the insurance industry and deliver services that contribute to customers' sustainable business |
Nov 15, 2024 09:13 HKT/SGT |
Fujitsu collaborates with global suppliers in decarbonization initiative to exchange product-level primary data on CO2 emissions |
Nov 13, 2024 11:38 HKT/SGT |
SoftBank Corp. and Fujitsu Strengthen Partnership for Realization of AI-RAN Commercialization |
Nov 12, 2024 12:57 HKT/SGT |
JA Mitsui Leasing and Fujitsu collaborate on simulation-driven field trials to optimize commercial EV adoption and drive decarbonization |
Nov 7, 2024 13:51 HKT/SGT |
Home of Fujitsu joint conservation project designated as first Nationally Certified Sustainably Managed Natural Site in Okinawa |
Nov 5, 2024 16:13 HKT/SGT |
Tokyo Stock Exchange and Fujitsu announce renewal of cash equity trading system 'arrowhead4.0' |
Nov 1, 2024 11:24 HKT/SGT |
Fujitsu's groundbreaking computing technology for accelerating scientific computing wins Japan Patent Office Commissioner's Award |
Nov 1, 2024 09:45 HKT/SGT |
Fujitsu and AMD to begin strategic partnership to develop more sustainable computing infrastructure intended to accelerate open-source AI initiatives |
Oct 30, 2024 12:43 HKT/SGT |
Fujitsu and Morinaga Milk Industry jointly develop a simulation system for raw material price fluctuations, speeding up decision-making |
More news >> |
|
|
|
|