Can humanoid robots guide older adults while walking in a way that feels both safe and comfortable?
And what kind of physical contact creates trust without causing additional stress?
The recent preprint study “Effects of Robotic Touch on Older Users During Walking Guidance by a Humanoid Robot” by Leonie Leven and colleagues from the Karlsruhe Institute of Technologie explores these questions.

Objectively Measuring Physiological Responses
Two movisens research sensors were used:

• The EcgMove 4 recorded a single-channel ECG at a sampling rate of 1,024 Hz. The data were used to calculate heart rate and the heart rate variability parameters RMSSD and pNN50.
• The EdaMove 4 captured electrodermal activity through two Ag/AgCl electrodes at a sampling rate of 32 Hz. The analysis included skin conductance level, the number of skin conductance responses, and their mean amplitude.

Gentle Physical Contact Receives a Positive Response
The ECG data indicated a slight tendency toward higher stress during the interaction with the robot: heart rate increased marginally, while the HRV parameters examined decreased slightly.
For electrodermal activity, the response amplitude was slightly higher in some of the contact-based conditions than during contactless guidance.
The subjective and behavioral findings were generally positive. Holding the robot and resting the forearm on it were particularly associated with greater perceived safety, trust, and comfort. The results therefore suggest that older adults may prefer gentle, stable touch during robot-assisted walking guidance to an entirely contactless interaction.

Multidimensional Research Under Realistic Conditions
The study demonstrates the value of a multimodal research approach. Questionnaires alone may reflect conscious evaluations and socially desirable responses. ECG and electrodermal activity complement these reports by capturing continuous and largely involuntary physiological reactions.
This is precisely where the movisens product portfolio offers a wide range of research possibilities. The EcgMove 4 combines ECG and physical activity monitoring in a mobile system. The EdaMove 4 combines electrodermal activity with movement and contextual information. These sensors allow researchers to collect raw data not only in the laboratory but also in ambulatory studies conducted in participants’ everyday lives. Via Bluetooth, selected live parameters can also be connected to the movisensXS experience sampling platform. This makes it possible, for example, to trigger questionnaires or interventions in response to physiological changes or activity-related events.
Building on this approach, future studies could investigate how the acceptance of assistive robots develops over longer periods and in real-world care or clinical settings. Combining objective biosignals, physical activity data, and situation-specific self-reports provides a particularly informative methodological foundation for this research.

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New Study validates the Activity Sensor Move 4 for Motion Analysis in Children and Young Adolescents Using Manual Wheelchairs
Objective movement measurement is a key prerequisite for evidence-based research. A recent study by Friedrich-Alexander University Erlangen-Nürnberg published in the Journal of NeuroEngineering and Rehabilitation marks an important milestone in this field. For the first time the movisens Move 4 - Activity Sensor has been validated and calibrated specifically for children and adolescents who use manual wheelchairs.

The aim of the study was to establish robust activity intensity thresholds ranging from sedentary behavior to vigorous wheelchair propulsion. Heart rate and energy expenditure were also measured as physiological reference parameters. The results demonstrate that the Move 4 accurately and reliably captures different levels of physical activity. In particular, the high measurement stability and the newly developed population-specific activity thresholds provide an important foundation for future research in inclusive physical activity and rehabilitation. These findings enable a more objective and precise assessment of physical activity and movement behavior in children and adolescents using manual wheelchairs.

Close collaboration between researchers and technology providers is a key factor in the success of projects like this. This collaboration enabled reliable data collection and laid the foundation for the successful validation of the system. We are proud that our technology contributes to innovative, practice-oriented research. Together with our scientific partners we are advancing objective movement analysis and helping to create new opportunities for research, rehabilitation, and evidence-based healthcare.

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Today, researchers studying the relationship between physical activity, movement, and mood in everyday life increasingly rely on movisens as a central part of their work.

What began as a combination of scientifically validated wearable sensors and innovative EMA technology has grown into an established infrastructure for behavioral and health research. Research teams around the world use movisens to measure experiences and behaviors where they actually happen—in people's daily lives.
A recent meta-analysis published in Nature Human Behaviour highlights movisens' role in the field. The study brings together findings from a large number of investigations examining the relationship between movement and mood and represents one of the most comprehensive analyses conducted to date. Notably, researchers carried out many of the included studies using movisens technology.
This achievement reflects more than the widespread adoption of sensors and apps. Over the years, researchers have built a shared ecosystem around movisens—one that supports comparable data, reproducible methods, and the integration of findings across studies.
Today, movisens delivers far more than sensor technology or EMA software. It provides a research infrastructure that makes real-world behavior and lived experiences measurable. Researchers use this infrastructure to understand the dynamics of human behavior beyond the laboratory and to answer questions that are becoming increasingly important for prevention, mental health, and personalized interventions.

If researchers want to understand real life, they must measure people in real life. Every day, movisens enables researchers around the world to do exactly that.

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