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sts.components.contact.mr.placeholder Sebastian Webel
Mr. Sebastian Webel

Editor-in-Chief

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Pictures of the Future
The Magazine for Research and Innovation
 

Demographic Change

Walker 2.0: Medical Assistant and Personal Trainer in One

FriWalk (Friendly Robot Walker) analyzes user gait patterns, thus motivating elderly people to engage in more physical activity through social interactions.

An innovative mobility aid recognizes the early signs of health risks based on the user’s gait; it thus functions as a personal trainer, motivating elderly people to be more active. Patients and medical professionals stand to benefit.

Everyone has a unique, individual way of walking. Even from far away, we can recognize people we know based on their gait. And a person’s gait also says a lot about his or her health. It is not always possible to visually determine whether a person’s gait pattern is healthy or an indication of a medical problem. Specially developed walkways are a common technical aid for medical diagnosis. The patient walks across the walkway multiple times and the pressure exerted with each step is measured using sensors. With the help of computers, details about his or her gait pattern are calculated based on gait phases. According to Josef Birchbauer from Siemens Corporate Technology, however, this method has a few disadvantages: “It creates an unnatural situation. The patient is being observed and feels like they are walking on a catwalk, which alters their normal gait pattern because naturally everyone tries to do their best. In addition, a walkway is costly and limited to a few meters in length,” says Birchbauer.

New Gait Analysis System

As part of the EU ACANTO (A CyberphysicAl social NeTwOrk) project, researchers from six European countries are working on “FriWalk,” a new gait analysis system. “FriWalk” (Friendly Robot Walker) consists of a four-wheeled walker that is equipped with depth sensors and cameras. During clinical analysis, the user wears special shoe inserts equipped with pressure sensors. FriWalk measures the precise position of the feet on the ground, their orientation, and the pressure exerted when the feet come into contact with the ground. Semantic information such as step length, step width, and gait rhythm is derived from these parameters. “We process 15 to 20 frames per second, which produces a virtual walkway on which we can see the footprints on the floor together with the corresponding pressure distribution as well as the path of motion of the feet in the air,” reports Birchbauer.

Walker as a Motivator

FriWalk is less expensive than a walkway and offers higher data quality. Much like a 24-hour EKG, the patient can use FriWalk for longer distances. This allows doctors to identify phenomena that may only occur after longer periods of strain.

FriTablet users can write information about their habits and preferences into the system. The information helps FriWalk suggest suitable physical activities based on the data.

 “Our goal is to have one version of the walker for hospitals and a less expensive version that costs less than €2,000 for families,” says project manager Luigi Palopoli, who works at the University of Trento in Italy. Beyond its medical diagnostics applications, FriWalk could also function as a personal trainer. Relatives, close friends, or the users themselves enter information about habits and preferences into a “FriTablet.” FriWalk recommends appropriate physical activities – such as visiting an exhibition or going on a shopping tour – based on the resulting user profile. However, the user’s interests are primarily identified from the observation of past situations in which the user’s physical and emotional state was measured. To this end, FriWalk is equipped with additional sensors such as a contactless heart rate monitor and systems that can identify emotions based on facial expressions. In addition, gesture recognition will make the device’s controls user-friendly.

Using Robots to Create a Cyberphysical Social Network

Doctors and medical professionals can define training goals based on the health data FriWalk collects. The software serves as a navigational aid during training and helps users to avoid potential hazards, such as slick spots on the ground and stressful situations such as crowded places. In order to achieve this, real-time information from sensors in the environment and from other FriWalkers is linked together and made accessible via a cloud-based infrastructure. This allows the system to quickly identify unexpected situations and inform the user about alternative options.

The goal is to create a cyberphysical social network – a communication system that connects user groups who share similar preferences with one another and displays where an interesting group activity is taking place. "It is important to ensure that the technology does not put too much stress on seniors,” says Birchbauer. “Our system is designed to look the same as a conventional walking aid, which is why we have made all the sensors as inconspicuous as possible.” Around 100 seniors in Spain, Italy, and England will test FriWalk until the project’s closing date in 2018. Special attention will be paid to data privacy. ACANTO is receiving €4.3 million in funding from the European Commission.

Wilma Mert