ExaWizards Group's ExaMD Starts Joint Research with Kobe University
ExaMD has begun a clinical study with Kobe University and Nishi Memorial Port Island Rehabilitation Hospital using its AI walking analysis app 'LocoStep' for post-knee surgery rehabilitation.
📋 Article Processing Timeline
- 📰 Published: April 8, 2026 at 17:30
- 🔍 Collected: April 8, 2026 at 09:00
- 🤖 AI Analyzed: April 20, 2026 at 20:51 (299h 51m after Collected)
ExaMD Inc. (Minato-ku, Tokyo, CEO: Hama, hereinafter "ExaMD"), a group company of ExaWizards Inc. (Minato-ku, Tokyo, Representative Director & CEO: Makoto Haruta), has launched a joint research project concerning gait analysis for patients undergoing total knee arthroplasty (TKA). The research is conducted in collaboration with Kobe University (Kobe City, Hyogo Prefecture, hereinafter "Kobe University") and Medical Corporation Yasuokai Nishi Memorial Port Island Rehabilitation Hospital (Kobe City, Hyogo Prefecture, hereinafter "Nishi Memorial Port Island Rehabilitation Hospital"), utilizing ExaMD's medical AI walking analysis app, "LocoStep."
In this joint research, the clinical efficacy and safety of a new gait analysis method utilizing AI will be verified, aiming to improve the quality of post-knee surgery rehabilitation and establish a gait evaluation method that is easy to use in practical clinical settings.
☑ Background
Total Knee Arthroplasty (TKA) is a typical surgical treatment for osteoarthritis of the knee, and the recovery of gait function post-surgery is directly linked to the patient's quality of life (QOL). On the other hand, conventional gait evaluation required expensive equipment such as 3D motion analysis systems, large spaces, specialized staff, and additional working hours, posing many restrictions on routine medical care and multi-center operations. In recent years, gait analysis technologies using smart devices and AI have been developing; however, data verifying their efficacy and safety based on clinical research designs, especially for TKA patients, is still insufficient. Given this background, we decided to conduct joint research involving three parties: Kobe University, Nishi Memorial Port Island Rehabilitation Hospital, and ExaMD, to leverage expertise in both clinical rehabilitation medicine and medical AI technology.
☑ Features of this Research
In this study, targeting TKA patients, we will verify "by what indicators" and "to what extent" AI-based gait analysis correlates with clinical evaluations, thereby clarifying its clinical value and effectiveness.
Simultaneously, we will explore evaluation methods that are easy to incorporate into daily clinical workflows. By uniting a medical AI startup with a university hospital and a specialized rehabilitation hospital, we aim to build evidence from the perspectives of both medical validity and implementation feasibility.
☑ Expected Outcomes
- Improved quality of post-TKA rehabilitation
- By clarifying the relationship between AI gait analysis indicators and clinical evaluations, it is expected to provide insights that contribute to planning appropriate rehabilitation and treatments.
- Standardization and efficiency of gait evaluation
- Quantifying evaluations via AI—which traditionally relied on the subjective views of experts—is expected to improve evaluation reproducibility, reduce time, and lessen the burden on personnel.
- Development of easy-to-use AI tools for medical settings
- Based on the findings of this research, we will accelerate product development with an eye toward implementation in medical institutions, proceeding with functional improvements to "LocoStep" and considering new features that meet clinical needs.
☑ Future Outlook
The findings obtained from this joint research are scheduled to be published through academic conferences and papers after the research period ends, complying with ethical, legal, and contractual conditions.
In this joint research, the clinical efficacy and safety of a new gait analysis method utilizing AI will be verified, aiming to improve the quality of post-knee surgery rehabilitation and establish a gait evaluation method that is easy to use in practical clinical settings.
☑ Background
Total Knee Arthroplasty (TKA) is a typical surgical treatment for osteoarthritis of the knee, and the recovery of gait function post-surgery is directly linked to the patient's quality of life (QOL). On the other hand, conventional gait evaluation required expensive equipment such as 3D motion analysis systems, large spaces, specialized staff, and additional working hours, posing many restrictions on routine medical care and multi-center operations. In recent years, gait analysis technologies using smart devices and AI have been developing; however, data verifying their efficacy and safety based on clinical research designs, especially for TKA patients, is still insufficient. Given this background, we decided to conduct joint research involving three parties: Kobe University, Nishi Memorial Port Island Rehabilitation Hospital, and ExaMD, to leverage expertise in both clinical rehabilitation medicine and medical AI technology.
☑ Features of this Research
In this study, targeting TKA patients, we will verify "by what indicators" and "to what extent" AI-based gait analysis correlates with clinical evaluations, thereby clarifying its clinical value and effectiveness.
Simultaneously, we will explore evaluation methods that are easy to incorporate into daily clinical workflows. By uniting a medical AI startup with a university hospital and a specialized rehabilitation hospital, we aim to build evidence from the perspectives of both medical validity and implementation feasibility.
☑ Expected Outcomes
- Improved quality of post-TKA rehabilitation
- By clarifying the relationship between AI gait analysis indicators and clinical evaluations, it is expected to provide insights that contribute to planning appropriate rehabilitation and treatments.
- Standardization and efficiency of gait evaluation
- Quantifying evaluations via AI—which traditionally relied on the subjective views of experts—is expected to improve evaluation reproducibility, reduce time, and lessen the burden on personnel.
- Development of easy-to-use AI tools for medical settings
- Based on the findings of this research, we will accelerate product development with an eye toward implementation in medical institutions, proceeding with functional improvements to "LocoStep" and considering new features that meet clinical needs.
☑ Future Outlook
The findings obtained from this joint research are scheduled to be published through academic conferences and papers after the research period ends, complying with ethical, legal, and contractual conditions.