More than step count: measuring how people move in daily life

The power of wearable measurement of mobility and physical activity

Mobility and physical activity are fundamental elements of healthy functioning. A recent study from UK Biobank showed that simply adding motion data from the wrist to baseline models improved classification of 52 diseases and longitudinal prediction of 26 diseases. This is remarkable. It underscores the potential of digital mobility and physical activity measures in the management and monitoring of health and disease. That potential is not limited to the wrist: sensors worn on the ankle, lower back or upper arm each capture a different perspective on how people move.

For more than a decade, activity trackers have been part of our daily lives. Many of us aim for 10,000 steps a day, which shows the scale at which these technologies are used. Research has followed: PubMed lists thousands of papers on actigraphy, a key technology behind digital mobility and physical activity measures. Yet their use in clinical research and care is still limited which is a missed opportunity.

Clinicians and researchers typically monitor mobility and physical activity through clinical assessments and questionnaires (examples shown in table below), capturing only a snapshot in time. Wearable-derived digital measures complement this through continuous monitoring in real-life settings, picking up subtle changes in how people move in everyday life.

Mobility and physical activity are relevant across diseases

Mobility and physical activity matter across a wide range of disease areas and life stages. They range from neuromuscular function in Parkinson’s disease and multiple sclerosis to walking capacity in heart failure and COPD and to frailty and fall risk in older adults.

The Digital Medicine Society (DiMe) has defined a core set of digital measures of physical activity that capture the measures that matter across diseases. In other words, if one is wants to select the right digital measure of mobility and physical activity in a specific disease or life stage, this is a good starting point. It distinguishes eight concepts that capture mobility and physical activity: lower limb strength, walking volume, walking speed, postural sway, full body changes in position, time spent in different intensity activities, upper limb range of motion, and upper limb strength.

To give an idea how this works: the non-exhaustive table below links each concept to disease areas where it matters, to the clinical measures used today, and to wearable-derived digital measures that complement these clinical assessments. It shows that digital measures are available for many mobility and physical activity concepts across disease.

*MDS-UPDRS: Movement Disorder Society–Unified Parkinson’s Disease Rating Scale

From in-clinic assessment to digital measures: the evidence is there

Of all digital measures, digital mobility and physical activity measures are backed by strong evidence. In clinical trials, stride velocity 95th centile (SV95C), measured with ankle-worn sensors, was the first wearable-derived endpoint qualified by the European Medicines Agency (EMA). EMA qualified it in 2019 as a secondary endpoint and in 2023 as a primary endpoint, for trials in ambulant patients with Duchenne muscular dystrophy.

These trials previously suffered from imperfect outcome measures, because established tests such as the 6-minute walk test are single snapshots taken in the clinic. Their results depend on motivation, fatigue and how a child feels on the day, and they say little about how these children move in daily life. SV95C allows a more sensitive measurement that is better suited to this population.

That the highest regulatory standard has been applied to a digital mobility and physical activity endpoint is promising. Similar digital outcome measures are now being developed and validated. The recently completed Mobilise-D project generated evidence for this type of measure, focusing on rigorous validation of real-world walking measures across therapeutic areas.

In healthcare, the evidence is more fragmented, but several local examples underscore the clinical utility of digital mobility and physical activity measures. The National Institute for Health and Care Excellence (NICE), for example, conditionally recommends five devices that collect mobility and physical activity data for remote monitoring of Parkinson’s disease. The condition is that real-world evidence on quality of life and resource use is generated and healthcare costs are managed.

Presenting TNO’s physical activity and mobility module

Mobility and physical activity are more than just step count. Wearable sensors on the wrist, ankle, lower back or upper arm hold valuable information for clinical research and disease management across disease areas, and the validated tools are there.

That is why we present a dedicated mobility and physical activity module on TNO’s remote data collection platform. The module enables researchers to collect validated digital mobility and physical activity measures remotely, continuously, and in real-world settings using wearable sensors.

Nevertheless, measuring mobility and physical activity in daily life does come with challenges. Participants need to wear a device correctly and long enough to yield meaningful data. Different devices and algorithms can give different results for the same measure. And a measure validated in one population is not automatically valid in another.

TNO helps address these challenges. We design studies that keep participant burden low, so data collection remains high. We select the right device and wear location for your question and population. And we deliver data analytics with algorithms validated for your context of use. That way, how people move in daily life becomes evidence you can rely on.