This study investigates how controllability of force is influenced by concurrent vibrotactile feedback that is generated proportionally to the applied force. Three different models to provide tactile ...feedback are introduced: amplitude and frequency modulation and granular synthesis. Then, an experiment investigating the effect of the feedback models on force control is reported. The tactile feedback conditions were compared to each other and to a condition with no feedback in a force repetition and a force hold tasks. In the force repetition task, all the feedback conditions yielded significantly better accuracy compared to no feedback condition. In the force hold task, there was no difference in the accuracy between the conditions including the no feedback condition. The results suggest that dynamic vibrotactile feedback assists the force control in force repetition tasks.
Abstract Background Many individuals with neurodegenerative (NDD) and immune-mediated inflammatory disorders (IMID) experience debilitating fatigue. Currently, assessments of fatigue rely on patient ...reported outcomes (PROs), which are subjective and prone to recall biases. Wearable devices, however, provide objective and reliable estimates of gait, an essential component of health, and may present objective evidence of fatigue. This study explored the relationships between gait characteristics derived from an inertial measurement unit (IMU) and patient-reported fatigue in the IDEA-FAST feasibility study. Methods Participants with IMIDs and NDDs (Parkinson's disease (PD), Huntington's disease (HD), rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), primary Sjogren’s syndrome (PSS), and inflammatory bowel disease (IBD)) wore a lower-back IMU continuously for up to 10 days at home. Concurrently, participants completed PROs (physical fatigue (PF) and mental fatigue (MF)) up to four times a day. Macro (volume, variability, pattern, and acceleration vector magnitude) and micro (pace, rhythm, variability, asymmetry, and postural control) gait characteristics were extracted from the accelerometer data. The associations of these measures with the PROs were evaluated using a generalised linear mixed-effects model (GLMM) and binary classification with machine learning. Results Data were recorded from 72 participants: PD = 13, HD = 9, RA = 12, SLE = 9, PSS = 14, IBD = 15. For the GLMM, the variability of the non-walking bouts length (in seconds) with PF returned the highest conditional R2, 0.165, and with MF the highest marginal R2, 0.0018. For the machine learning classifiers, the highest accuracy of the current analysis was returned by the micro gait characteristics with an intrasubject cross validation method and MF as 56.90% (precision = 43.9%, recall = 51.4%). Overall, the acceleration vector magnitude, bout length variation, postural control, and gait rhythm were the most interesting characteristics for future analysis. Conclusions Counterintuitively, the outcomes indicate that there is a weak relationship between typical gait measures and abnormal fatigue. However, factors such as the COVID-19 pandemic may have impacted gait behaviours. Therefore, further investigations with a larger cohort are required to fully understand the relationship between gait and abnormal fatigue.
Problems with fatigue and sleep are highly prevalent in patients with chronic diseases and often rated among the most disabling symptoms, impairing their activities of daily living and the ...health-related quality of life (HRQoL). Currently, they are evaluated primarily
via
Patient Reported Outcomes (PROs), which can suffer from recall biases and have limited sensitivity to temporal variations. Objective measurements from wearable sensors allow to reliably quantify disease state, changes in the HRQoL, and evaluate therapeutic outcomes. This work investigates the feasibility of capturing continuous physiological signals from an electrocardiography-based wearable device for remote monitoring of fatigue and sleep and quantifies the relationship of objective digital measures to self-reported fatigue and sleep disturbances. 136 individuals were followed for a total of 1,297 recording days in a longitudinal multi-site study conducted in free-living settings and registered with the German Clinical Trial Registry (DRKS00021693). Participants comprised healthy individuals (
N
= 39) and patients with neurodegenerative disorders (NDD,
N
= 31) and immune mediated inflammatory diseases (IMID,
N
= 66). Objective physiological measures correlated with fatigue and sleep PROs, while demonstrating reasonable signal quality. Furthermore, analysis of heart rate recovery estimated during activities of daily living showed significant differences between healthy and patient groups. This work underscores the promise and sensitivity of novel digital measures from multimodal sensor time-series to differentiate chronic patients from healthy individuals and monitor their HRQoL. The presented work provides clinicians with realistic insights of continuous at home patient monitoring and its practical value in quantitative assessment of fatigue and sleep, an area of unmet need.
Background: Innovative Medicines Initiative (IMI) consortium IDEA-FAST is developing novel digital measures of fatigue, sleep quality, and impact of sleep disturbances for neurodegenerative diseases ...and immune-mediated inflammatory diseases. In 2022, the consortium met with the European Medicines Agency (EMA) to receive advice on its plans for regulatory qualification of the measures. This viewpoint reviews the IDEA-FAST perspective on developing digital measures for multiple diseases and the advice provided by the EMA. Summary: The EMA considered a cross-disease measure an interesting and arguably feasible concept. Developers should account for the need for a strong rationale that the clinical features to be measured are similar across diseases. In addition, they may expect increased complexity of study design, challenges when managing differences within and between disease populations, and the need for validation in both heterogeneous and homogeneous populations. Key Messages: EMA highlighted the challenges teams may encounter when developing a cross-disease measure, though benefits potentially include reduced resources for the technology developer and health authority, faster access to innovation across different therapeutic fields, and feasibility of cross-disease comparisons. The insights included here can be used by project teams to guide them in the development of cross-disease digital measures intended for regulatory qualification.
Fatigue is a prominent symptom in many diseases and is strongly associated with impaired daily function. The measurement of daily function is currently almost always done with questionnaires, which ...are subjective and imprecise. With the recent advances of digital wearable technologies, novel approaches to evaluate daily function quantitatively and objectively in real-life conditions are increasingly possible. This also creates new possibilities to measure fatigue-related changes of daily function using such technologies.
This review examines which digitally assessable parameters in immune-mediated inflammatory and neurodegenerative diseases may have the greatest potential to reflect fatigue-related changes of daily function.
Results of a standardized analysis of the literature reporting about perception-, capacity-, and performance-evaluating assessment tools indicate that changes of the following parameters: physical activity, independence of daily living, social participation, working life, mental status, cognitive and aerobic capacity, and supervised and unsupervised mobility performance have the highest potential to reflect fatigue-related changes of daily function. These parameters thus hold the greatest potential for quantitatively measuring fatigue in representative diseases in real-life conditions, e.g., with digital wearable technologies. Furthermore, to the best of our knowledge, this is a new approach to analysing evidence for the design of performance-based digital assessment protocols in human research, which may stimulate further systematic research in this area.
Traditionally only speech communicates emotions via mobile phone. However, in daily communication the sense of touch mediates emotional information during conversation. The present aim was to study ...if tactile stimulation affects emotional ratings of speech when measured with scales of pleasantness, arousal, approachability, and dominance. In the Experiment 1 participants rated speech-only and speech-tactile stimuli. The tactile signal mimicked the amplitude changes of the speech. In the Experiment 2 the aim was to study whether the way the tactile signal was produced affected the ratings. The tactile signal either mimicked the amplitude changes of the speech sample in question, or the amplitude changes of another speech sample. Also, concurrent static vibration was included. The results showed that the speech-tactile stimuli were rated as more arousing and dominant than the speech-only stimuli. The speech-only stimuli were rated as more approachable than the speech-tactile stimuli, but only in the Experiment 1. Variations in tactile stimulation also affected the ratings. When the tactile stimulation was static vibration the speech-tactile stimuli were rated as more arousing than when the concurrent tactile stimulation was mimicking speech samples. The results suggest that tactile stimulation offers new ways of modulating and enriching the interpretation of speech.
What is a device bend gesture really good for? Ahmaniemi, Teemu T.; Kildal, Johan; Haveri, Merja
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems,
04/2014
Conference Proceeding
Device deformation allows new types of gestures to be used in interaction. We identify that the gesture/use-case pairings proposed by interaction designers are often driven by factors relating ...improved tangibility, spatial directionality and strong metaphorical bonds. With this starting point, we argue that some of the designs may not make use of the full potential of deformation gestures as continuous, bipolar input techniques. In two user studies, we revisited the basics of deformation input by taking a new systematic look at the question of matching gestures with use cases. We observed comparable levels of UX when using bend input in different continuous bipolar interactions, irrespective of the choice of tangibility, directionality and metaphor. We concluded that device bend gestures use their full potential when used to control continuous bipolar parameters, and when quick reactions are needed. From our studies, we also identify relative strengths of absolute and relative mappings, and report a Fitts' law study for device bending input.
This paper describes a method for creating virtual textures without force feedback by using a simple motion sensor and a single vibrotactile actuator. It is based on wavetable synthesis driven by the ...user's hand movements. The output of the synthesis is rendered with the tactile actuator attached in a hand-held box together with the motion sensor. The method provides a solution for creating tangible properties for virtual objects which can be explored by pointing at them with the sensor-actuator device. The study introduces 12 virtual textures which were based on three different envelope ridge lengths, two spatial densities, and were either regularly or irregularly organized. To evaluate the role of each design parameter in the perception of the texture, a series of experiments was conducted. The perceived similarity was assessed in a pairwise comparison test and the outcome was analyzed by using multidimensional scaling. The analysis revealed that envelope ridge length and spatial density were distinguishable design parameters while regularity was not. The textures were also rated according to five attribute scales previously determined in the pilot experiment. The results show that ridge length and spatial density influence perceived roughness and flatness similarly as with real textures.
Systolic time intervals Pre-Ejection Period (PEP) and Left Ventricular Ejection Time (LVET) are widely used indicators of cardiac functions. While accurate assessment of them requires costly ...equipment such as echocardiography devices, a satisfactory estimation can be done by analyzing signals from simple accelerometer and microphone attached to human chest. This paper reports a study where heart rate and the systolic intervals were derived from phonocardiogram (PCG) and seismocardiogram (SCG) simultaneously. Both sensors, the microphone for PCG and the accelerometer for SCG were attached on the chest wall, close to sternum (PCG) and apex of the heart (SCG). The signals were acquired from 10 participants in a 33-minute laboratory protocol with synchronized ECG measurements. Both signals went through an identical processing path: band pass filtering, envelope extraction with Hilbert transformation and peak detection from the envelope signal. In heart rate estimation, PCG and SCG reached 84% and 93% accuracy, respectively. The systolic interval accuracy estimation was based on deviation analysis as the absolute reference values for PEP and LVET were not available. In PEP estimation, the average standard deviations during the rest periods of the protocol were 4 ms for PCG and 8 ms for SCG. In LVET estimation, the deviations were nearly 10 fold compared to PEP. However, the results show that both methods can be used for accurate heart rate estimation and with careful mechanical attachment also PEP can be accurately derived from both. Due to sharper envelope signal waveform, PEP estimation was more accurate with PCG than with SCG.
In this study, pulse arrival time (PAT) was measured using a simple measurement setup consisting of arm electrocardiogram (ECG) and finger photoplethysmogram (PPG). Four methods to calculate PAT from ...the measured signals were evaluated. PAT was calculated as the time delay between ECG R peak and one of the following points in the PPG waveform: peak (maximum value of PPG waveform), foot (minimum value of PPG waveform), dpeak (maximum value of the first derivative of PPG waveform) and ddpeak (maximum value of the second derivative of PPG waveform). In addition to PAT calculation, pulse period (PP) intervals based on the detected features were determined and compared to RR intervals derived from ECG signal. Based on the results obtained here, the most promising method to be used in PAT or PP calculation seems to be the dpeak detection method.
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