The association between peripheral neuropathy and daily-life gait quality characteristics in people with diabetes.

Background: Peripheral neuropathy is a common complication of diabetes and increases the risk of falls, possibly through gait (quality) impairments in daily life. Characteristics of gait quality have been associated with peripheral neuropathy in a laboratory setting, but little is known about the more relevant association with gait quality in daily life.

Research Question: What is the association between peripheral neuropathy and gait quality characteristics in daily life in people with diabetes?

Methods: Data from two cross-sectional studies were combined in an exploratory analysis, including a total of 98 participants with diabetes (mean age: 68 (SD 7) years, 32 females), of which 68 with peripheral neuropathy.

Real-World Gait Detection Using a Wrist-Worn Inertial Sensor: Validation Study.

Background: Wrist-worn inertial sensors are used in digital health for evaluating mobility in real-world environments. Preceding the estimation of spatiotemporal gait parameters within long-term recordings, gait detection is an important step to identify regions of interest where gait occurs, which requires robust algorithms due to the complexity of arm movements. While algorithms exist for other sensor positions, a comparative validation of algorithms applied to the wrist position on real-world data sets across different disease populations is missing.

Translating digital healthcare to enhance clinical management: a protocol for an observational study using a digital health technology system to monitor medication adherence and its effect on mobility in people with Parkinson's.

Introduction: In people with Parkinson's (PwP) impaired mobility is associated with an increased falls risk. To improve mobility, dopaminergic medication is typically prescribed, but complex medication regimens result in suboptimal adherence. Exploring medication adherence and its impact on mobility in PwP will provide essential insights to optimise medication regimens and improve mobility.

Feasibility and usability of a digital health technology system to monitor mobility and assess medication adherence in mild-to-moderate Parkinson's disease.

Introduction: Parkinson's disease (PD) is a neurodegenerative disorder which requires complex medication regimens to mitigate motor symptoms. The use of digital health technology systems (DHTSs) to collect mobility and medication data provides an opportunity to objectively quantify the effect of medication on motor performance during day-to-day activities. This insight could inform clinical decision-making, personalise care, and aid self-management.

Multidomain cognitive training increases physical activity in people with Parkinson's disease with mild cognitive impairment.

Introduction: Cognitive impairment in Parkinson's disease (PD), especially in patients with mild cognitive impairment (PD-MCI), coincides with less physical activity. Cognitive trainings (CT) have been found to promote laboratory environment-based movement. Knowledge about their effect in natural home-based environment, reflecting everyday function, is sparse.

Connecting real-world digital mobility assessment to clinical outcomes for regulatory and clinical endorsement-the Mobilise-D study protocol.

Background: The development of optimal strategies to treat impaired mobility related to ageing and chronic disease requires better ways to detect and measure it. Digital health technology, including body worn sensors, has the potential to directly and accurately capture real-world mobility. Mobilise-D consists of 34 partners from 13 countries who are working together to jointly develop and implement a digital mobility assessment solution to demonstrate that real-world digital mobility outcomes have the potential to provide a better, safer, and quicker way to assess, monitor, and predict the efficacy of new interventions on impaired mobility.

Technical validation of real-world monitoring of gait: a multicentric observational study.

Introduction: Existing mobility endpoints based on functional performance, physical assessments and patient self-reporting are often affected by lack of sensitivity, limiting their utility in clinical practice. Wearable devices including inertial measurement units (IMUs) can overcome these limitations by quantifying digital mobility outcomes (DMOs) both during supervised structured assessments and in real-world conditions. The validity of IMU-based methods in the real-world, however, is still limited in patient populations.

Free-Living Standing Activity as Assessed by Seismic Accelerometers and Cognitive Function in Community-Dwelling Older Adults: The MIND Trial.

Background: Few older adults are able to achieve recommended levels of moderate-vigorous physical activity despite known cognitive benefits. Alternatively, less intense activities such as standing can be easily integrated into daily life. No existing study has examined the impact of free-living standing activity during daily life as measured by a device on cognition in older adults.

Older Adults with Weaker Muscle Strength Stand up from a Sitting Position with More Dynamic Trunk Use.

The ability to stand up from a sitting position is essential for older adults to live independently. Body-fixed inertial sensors may provide an approach for quantifying the sit-to-stand (STS) in clinical settings. The aim of this study was to determine whether measurements of STS movements using body-fixed sensors yield parameters that are informative regarding changes in STS performance in older adults with reduced muscle strength.

Effect of bed height and use of hands on trunk angular velocity during the sit-to-stand transfer.

Unlabelled: The ability to rise from a chair or bed is critical to an individual's quality of life because it determines functional independence. This study was to investigate the effect of bed height and use of hands on trunk angular velocity and trunk angles during the sit-to-stand (STS) performance. Twenty-four older persons (median age 74 years) were equipped with a body-fixed gyroscopic sensor and stood up from a bed adjusted to different heights, with and without the use of hands at each height.