Mattia Corzani

Objective: To assess the feasibility and, preliminarily, the effectiveness of long-term, personalized gait training using a digital wearable system (Gait Tutor) that provides real-time audio biofeedback to correct or reinforce gait behaviour. Design: Open-label and non-controlled, with assessments before and after intervention. Setting: Real-world. Participants: Twenty persons with Parkinson's disease. Intervention: Participants performed home-based gait training in their ON medication state for 30 minutes, 3 times per week, for 9 months using a Gait Tutor. Main measures: We evaluated adherence (% of expected sessions), usability, and, preliminarily, efficacy by assessing the motor performance of the participants before and after the intervention. Results: Seventeen participants (85%) completed the study, performing an average of 83 sessions. Adherence was higher for persons with an intermediate disease stage (80.5% of expected training sessions), compared to those with a more advanced disease stage (46.2%). All participants reported extremely positive scores on the questionnaire about ease of use and effectiveness (4.37 ± 0.42). The Movement Disorders Unified Parkinson's Disease Rating Scale motor scores remained stable after the training (mean 9 months). In people with an intermediate disease stage, clinical scores and physical capacity tended to improve. Conclusions: For the first time, this study shows the feasibility of long-term real-world gait training for people with Parkinson's disease, providing preliminary evidence that personalized, technology-driven rehabilitation strategies can be sustained over extended periods and can assist clinicians in objectively assessing gait performance in the real world.

Recent advances in mobile technology have shown that augmented unisensory feedback can be leveraged to improve gait using wearable systems, but less is known about the possible benefits and usability of multisensory (i.e., multimodal) feedback. This paper introduces the preliminary results of an innovative research project aiming to develop an mHealth system including Android smart glasses, and providing multisensory cues for gait rehabilitation of people affected by Parkinson’s disease in and out of the medical context. In particular, the paper describes a preliminary pilot focusing on the design of visual, auditory, and haptic cues, and testing the design methodologies to be used in further developments of the project. Considered research questions were: Which kinds of images, sounds, and vibrations mostly influence gait speed, stride length, and cadence? Which are the ones stressing the user the least? Which ones induce the most immediate reaction? Thus, in this starting part of the research project, different typologies of sensory cues were designed, tested, and evaluated considering quantitative and qualitative parameters to properly answer the research questions.

Touchscreen devices are widely used in modern life and have quickly become part of daily life for children, including during Occupational Therapy sessions for children with disabilities. Touchscree...

This paper describes the second part of the PASSO (Parkinson smart sensory cues for older users) project, which designs and tests an innovative haptic biofeedback system based on a wireless body sensor network using a smartphone and different smartwatches specifically designed to rehabilitate postural disturbances in persons with Parkinson’s disease. According to the scientific literature on the use of smart devices to transmit sensory cues, vibrotactile feedback (particularly on the trunk) seems promising for improving people’s gait and posture performance; they have been used in different environments and are well accepted by users. In the PASSO project, we designed and developed a wearable device and a related system to transmit vibrations to a person’s body to improve posture and combat impairments like Pisa syndrome and camptocormia. Specifically, this paper describes the methodologies and strategies used to design, develop, and test wearable prototypes and the mHealth system. The results allowed a multidisciplinary comparison among the solutions, which led to prototypes with a high degree of usability, wearability, accessibility, and effectiveness. This mHealth system is now being used in pilot trials with subjects with Parkinson’s disease to verify its feasibility among patients.

Background: Objective measures of physical function in older adults are widely used to predict health outcomes such as disability, institutionalization, and mortality. App-based clinical tests allow users to assess their own physical function and have objective tracking of changes over time by use of their smartphones. Such tests can potentially guide interventions remotely and provide more detailed prognostic information about the participant’s physical performance for the users, therapists, and other health care personnel. We developed 3 smartphone apps with instrumented versions of the Timed Up and Go (Self-TUG), tandem stance (Self-Tandem), and Five Times Sit-to-Stand (Self-STS) tests. Objective: This study aimed to test the usability of 3 smartphone app–based self-tests of physical function using an iterative design. Methods: The apps were tested in 3 iterations: the first (n=189) and second (n=134) in a lab setting and the third (n=20) in a separate home-based study. Participants were healthy adults between 60 and 80 years of age. Assessors observed while participants self-administered the tests without any guidance. Errors were recorded, and usability problems were defined. Problems were addressed in each subsequent iteration. Perceived usability in the home-based setting was assessed by use of the System Usability Scale, the User Experience Questionnaire, and semi-structured interviews. Results: In the first iteration, 7 usability problems were identified; 42 (42/189, 22.0%) and 127 (127/189, 67.2%) participants were able to correctly perform the Self-TUG and Self-Tandem, respectively. In the second iteration, errors caused by the problems identified in the first iteration were drastically reduced, and 108 (108/134, 83.1%) and 106 (106/134, 79.1%) of the participants correctly performed the Self-TUG and Self-Tandem, respectively. The first version of the Self-STS was also tested in this iteration, and 40 (40/134, 30.1%) of the participants performed it correctly. For the third usability test, the 7 usability problems initially identified were further improved. Testing the apps in a home setting gave rise to some new usability problems, and for Self-TUG and Self-STS, the rates of correctly performed trials were slightly reduced from the second version, while for Self-Tandem, the rate increased. The mean System Usability Scale score was 77.63 points (SD 16.1 points), and 80-95% of the participants reported the highest or second highest positive rating on all items in the User Experience Questionnaire. Conclusions: The study results suggest that the apps have the potential to be used to self-test physical function in seniors in a nonsupervised home-based setting. The participants reported a high degree of ease of use. Evaluating the usability in a home setting allowed us to identify new usability problems that could affect the validity of the tests. These usability problems are not easily found in the lab setting, indicating that, if possible, app usability should be evaluated in both settings. Before being made available to end users, the apps require further improvements and validation.

BACKGROUND Objective measures of physical function in older adults are widely used to predict health outcomes such as disability, institutionalization, and mortality. App-based clinical tests allow users to assess their own physical function and have objective tracking of changes over time by use of their smartphones. Such tests can potentially guide interventions remotely and provide more detailed prognostic information about the participant’s physical performance for the users, therapists, and other health care personnel. We developed 3 smartphone apps with instrumented versions of the Timed Up and Go (Self-TUG), tandem stance (Self-Tandem), and Five Times Sit-to-Stand (Self-STS) tests. OBJECTIVE This study aimed to test the usability of 3 smartphone app–based self-tests of physical function using an iterative design. METHODS The apps were tested in 3 iterations: the first (n=189) and second (n=134) in a lab setting and the third (n=20) in a separate home-based study. Participants were healthy adults between 60 and 80 years of age. Assessors observed while participants self-administered the tests without any guidance. Errors were recorded, and usability problems were defined. Problems were addressed in each subsequent iteration. Perceived usability in the home-based setting was assessed by use of the System Usability Scale, the User Experience Questionnaire, and semi-structured interviews. RESULTS In the first iteration, 7 usability problems were identified; 42 (42/189, 22.0%) and 127 (127/189, 67.2%) participants were able to correctly perform the Self-TUG and Self-Tandem, respectively. In the second iteration, errors caused by the problems identified in the first iteration were drastically reduced, and 108 (108/134, 83.1%) and 106 (106/134, 79.1%) of the participants correctly performed the Self-TUG and Self-Tandem, respectively. The first version of the Self-STS was also tested in this iteration, and 40 (40/134, 30.1%) of the participants performed it correctly. For the third usability test, the 7 usability problems initially identified were further improved. Testing the apps in a home setting gave rise to some new usability problems, and for Self-TUG and Self-STS, the rates of correctly performed trials were slightly reduced from the second version, while for Self-Tandem, the rate increased. The mean System Usability Scale score was 77.63 points (SD 16.1 points), and 80-95% of the participants reported the highest or second highest positive rating on all items in the User Experience Questionnaire. CONCLUSIONS The study results suggest that the apps have the potential to be used to self-test physical function in seniors in a nonsupervised home-based setting. The participants reported a high degree of ease of use. Evaluating the usability in a home setting allowed us to identify new usability problems that could affect the validity of the tests. These usability problems are not easily found in the lab setting, indicating that, if possible, app usability should be evaluated in both settings. Before being made available to end users, the apps require further improvements and validation.

Wearable sensing technology is a new way to deliver corrective feedback. It is highly applicable to gait rehabilitation for persons with Parkinson’s disease (PD) because feedback potentially engages spared neural function. Our study characterizes participants’ motor adaptation to feedback signaling a deviation from their normal cadence during prolonged walking, providing insight into possible novel therapeutic devices for gait re-training. Twenty-eight persons with PD (15 with freezing, 13 without) and 13 age-matched healthy elderly (HE) walked for two 30-minute sessions. When their cadence varied, they heard either intelligent cueing (IntCue: bouts of ten beats indicating normal cadence) or intelligent feedback (IntFB: verbal instruction to increase or decrease cadence). We created a model that compares the effectiveness of the two conditions by quantifying the number of steps needed to return to the target cadence for every deviation. The model fits the short-term motor responses to the external step inputs (collected with wearable sensors). We found some significant difference in motor adaptation among groups and subgroups for the IntCue condition only. Both conditions were instead able to identify different types of responders among persons with PD, although showing opposite trends in their speed of adaptation. Increasing rather than decreasing the pace appeared to be more difficult for both groups. In fact, under IntFB the PD group required about seven steps to increase their cadence, whereas they only needed about three steps to decrease their cadence. However, it is important to note that this difference was not significant; perhaps future work could include more participants and/or more sessions, increasing the total number of deviations for analysis. Notably, a significant negative correlation, r = −0.57 (p-value = 0.008), was found between speed of adaptation and number of deviations during IntCue, but not during IntFB, suggesting that, for people who struggle with gait, such as those with PD, verbal instructions rather than metronome beats might be more effective at restoring normal cadence. Clinicians and biofeedback developers designing novel therapeutic devices could apply our findings to determine the optimal timing for corrective feedback, optimizing gait rehabilitation while minimizing the risk of cue-dependency.