## 3 Medical Aspects of Smart Shoes for Digital Health  
Gait impairment is a common symptom in several diseases, and affects activities of daily living and quality of life [65; 68; 84]. Among others, diseases with typical gait impairments are PD, multiple sclerosis (MS), cerebral palsy (CP), osteoarthritis, rheumatism, spinal cord disorders, and sarkopenia. Quantitative gait assessment of activity patterns has the potential to support clinical diagnostics and therapeutic decisions [85], compensating for the fact that clinical motor assessments are subjective in that they vary between investigators and depend on the experience of clinicians [86]. Sensor-based, mobile gait systems are able to provide objective, spatiotemporal gait parameters recorded in a flexible environment without being limited to motion labs, such as those measures found using gait analysis carpets or high-precision three-dimensional (3D)-motion capture systems. Wearable sensors have been shown to provide congruent results in patient cohorts with good accuracy and precision compared to gold-standard laboratory systems [27; 87]. As an example for typical gait impairment, patients suffering from PD show four cardinal symptoms: bradykinesia, rigor, tremor, and postural instability [88]. These major symptoms, with the exception of tremor, affect gait and consequently PD disease characteristics are associated with gait impairment. The clinical gold standard in rating motor symptoms is the Unified Parkinson Disease Rating Scale Part III (UPDRS-III) as described from the Movement Disorder Society [89]. However, since only 2 out of 16 items of the UPDRS-III assess walking tasks, gait is under-represented in this clinical score, and complementary measures are necessary. Sensor-based gait analysis systems are able to close this gap (Figure 7). Gait and mobility are strongly correlated with quality of life (QoL) in PD, as summarized in several reviews [66; 90; 91]. Objective gait assessment supports not only the clinical diagnostic workup in PD, but also provides monitoring measures in the course of the disease to reflect the severity of motor impairment and thus QoL. With disease progression, PD patients develop motor fluctuations during the day, and thus depend on timely medication intake and monitoring of the therapeutic effects on their mobility [74]. Home monitoring approaches could cover this range of gait mobility over the course of the day, and serve as complementary technology with the aim to optimize multidisciplinary medical care concepts for PD patients. For this purpose, the measured physical and physiological data need to go  
Figure 7: Clinical diagnosis based on the Unified Parkinson Disease Rating Scale, part III motor score (UPDRS-III) is not able to adequately reflect all gait impairments that occur in Parkinson’s disease (PD). An instrumented gait analysis complements clinical assessment by providing different objective parameters evaluating the broad spectrum of gait disturbances in PD. beyond pure smart shoe applications, and other biosignals (speech, upper extremity, sleep,... ) need to be investigated. This has, for example, been extensively discussed in [92]. In a pilot study, a telemedical application that allows PD patients to attend clinical appointments via video conference at home has been evaluated with 34 PD patients using a patient satisfaction questionnaire. PD patients' self-reporting revealed that the average costs related to the travel to the doctor could be reduced by $200, and commute time by 209 min [93]. This supports that telemedicine is a cost- and time-effective approach. Another group developed an instrumented Timed Up and Go test (iTUG) supported by wearable sensors to receive complementary information by analyzing gait characteristics in different test phases (i.e., sit-to-stand, walking, turning, and turn-to-sit) instead of just interpreting the time patients take to complete the test [94; 95]. The iTUG was assessed in PD subjects and controls in a laboratory as well as in a home environment.