The combination of artificial intelligence (AI) and wearable technology has fundamentally changed the practice of physiotherapy for oncology patients who need continuous, personalized and flexible rehabilitation-tailored strategies. Cancer and its treatments are associated with long-lasting disabling changes, especially with respect to mobility, which includes chronic inactivity, muscle atrophy and imbalance. These disorders need long-lasting physiotherapy management, particularly focused on the patient’s condition. Traditional physiotherapy has its benefits, but often in cancer survivors, it struggles with real-time remote monitoring, timely feedback and individual modifications needed for achieving the best outcomes. The development of AI-integrated wearable technologies allows continuous monitoring of patients’ physiological and biomechanical parameters and holds great potential in this regard. Embedding sensors such as accelerometers, gyroscopes and even electromyography (EMG) enables real-time collection and analysis of movement, activity and muscular activity data. Machine learning can use this data for creating personalized rehabilitation plans that adjust based on the patient’s progress. In this review, we study the impact of AI on physiotherapy technologies using wearables for oncology patients. We investigate recent innovations in technologies, application fields, wearable sensor types and machine learning techniques relevant for this purpose. In addition, we examine the clinical outcomes documented in recent studies, which include enhanced functional mobility, rehabilitation protocol compliance and satisfaction levels among patients. We pinpoint fundamental implementation hurdles including civil data, device user-friendliness and the requirement of specialist education. To conclude, we suggest more adaptable, reliable and efficient physiotherapy approaches for cancer patients which promote better integration with the recovery process. Around the world, cancer continues to be an enormous threat to public health. In addition to claiming millions of lives every year, it greatly diminishes the quality of life for those who survive. As per WHO statistics, cancer is a major contributor to mortality and morbidity globally with an approximate death toll of ten million each year. Despite advancements in screening, targeted molecular therapies, immunotherapy and precision medicine raising the survival prospects of many patients, such medical progress is also associated with new hurdles (Llovet et al. 2018). Perhaps the most concerning issue among cancer survivors is the existence of physical limitations in function as a result of the disease or its treatment. Survivors often report a variety of debilitating complications such as chronic fatigue, reduced mobility, peripheral neuropathy, lymphedema and generalized muscle weakness. All of these complications can significantly reduce our ability to perform simple everyday household tasks, live independently and enjoy a satisfactory life. Physiotherapy is now regarded as an indispensable part of healthcare for cancer patients requiring rehabilitation. The goal of physiotherapy is to restore optimal capacity, reduce pain, improve movement, and enhance health and mental wellness (Baldania and Baladaniya 2024). Despite the advantages it offers, standard physiotherapy techniques in oncology care have a number of important obstacles that need to be addressed. Traditional physiotherapy practices as a whole, and especially in lower- and middle-income regions, are often restricted by a shortage of healthcare services. Individual appointments with licensed physiotherapists are often not available to all patients, especially those who are elderly and live in rural or poorly serviced regions. Even in well-resourced settings, the growing population of cancer survivors can put a strain on rehabilitation resources. Moreover, traditional physiotherapy is often based on subjective evaluation techniques (Barth 2023). A substantial proportion of therapy’s clinical assessments rely on a therapist’s examination and the patient’s subjective responses, which, although helpful, are often inadequate in portraying the extent of functional limitation or change over time. Important mechanisms to control patient monitoring and adjust therapy dynamically to ensure optimal outcomes are also absent. The use of AI and related technology wearables offers solutions to some of the problems faced in rehabilitation healthcare. AI and wearables can transform physiotherapy in oncology by improving its accessibility, engagement, objectivity, customization and personalization. Smart watches, fitness trackers and even certain medical sensors qualify as wearables which continuously monitor biological and biomechanical metrics. These devices can continuously monitor heart rate, respiratory rate, step count, gait patterns and even posture. These devices, when used with proper interpretation techniques, provide a patient’s physical state in a longitudinal manner which is objective and accurate (Ball et al. 2014). Wearable devices are capable of generating big data, which can be processed by AI algorithms with the help of machine learning (ML) and deep learning frameworks. These algorithms are designed to identify patterns, predict results and reveal anomalies with a level of accuracy far beyond human observation (Zhang et al. 2020). In the case of physiotherapy, AI can be used to create rehabilitation programs tailored to respond adaptively to the patient’s movements and their specific requirements. An AI system, for instance, could monitor signs of muscle fatigue and an abnormal gait, and could modify the exercise regimen in real time. This intelligent feedback loop not only provides effective yet safe therapeutic care but also empowers the patient to play an active role in their rehabilitation. The integration of AI with wearable technology for the rehabilitation of cancer patients has shown its promise in various practical scenarios. As an example, IMU systems have been used to capture the gait and balance of chemo-received cancer patients, yielding insights into mobility impairments. Similarly, exercise-induced muscle activation can be monitored with wearable EMG sensors, which enhances evaluation of muscle function. Along with other technologies such as tele-rehabilitation systems, these approaches help clinicians formulate specific treatment plans, but are especially beneficial for patients who cannot physically attend therapy sessions (Algarni et al. 2022). Additionally, AI systems can automatically provide comprehensive evaluations and recommendations by analyzing data from multiple sources, such as wearable sensors, electronic health records and patient-reported data. Contribution from NLP helps enrich the understanding of patients by analyzing clinical notes and patient feedback documenting their therapeutic journey, which assists in providing a more detailed view of how patients are responding to their therapy. With the help of modern cloud-based platforms and mobile applications, feedback, prompts and encouragement can be provided through mobile devices, further aiding patients’ compliance. Even with the advancements, it is clear that numerous issues have yet to be tackled in order to integrate AI and wearable technology fully into oncology physiotherapy. The protection of data privacy and security, particularly around sensitive health data, continues to be a prime concern. Meeting standard requirements, such as HIPAA and GDPR, poses a challenge (Yigzaw et al. 2022). Other relevant issues include sensor precision, battery life, ease of use and user comfort, which impact the reliability and functionality of the wearable systems on a technical level. With respect to AI, providing access to algorithms and ensuring that they are easy to understand are important. AI-powered resources in practice and other clinical settings should be accessible, but in order for such tools to be accepted into clinical workflows, clinicians need to understand the logic behind the recommendations provided. Additionally, constructing reliable AI models involves obtaining large-scale datasets that capture myriad population groups. A lack of ethnoracial and demographic diversity presents limitations to the generalizability of most studies and sample designs. Also, carefully governing ethical concerns such as decision-making, autonomy, biases and discrimination is crucial (Call et al. 2023). Looking into the future, the integration of clinicians, patients, engineers and data scientists will be the most important component for advancement in this field. There is a need for great attention in the research and development of easily applicable, evidence-based, clinically tested and bound commercial solutions which function within the framework of the healthcare system infrastructure. The system also requires new teaching materials and instructional courses for healthcare professionals, which equip them with the skills to use these technologies easily and competently. Cancer rehabilitation is an integral aspect of the cancer care continuum and is designed to restore, as much as possible, the physical, psychological and social functioning of individuals with cancer. The type and stage of cancer, treatment modalities, along with the patient’s age, comorbidities and baseline physical state, determine the range of physical impairments experienced by the patient. It is clear, however, that there exist a number of common physical difficulties faced by various cancer populations. Another of the most frequently reported problems concerns cancer-related fatigue (CRF). CRF is often described as an unwavering, subjective feeling of exhaustion and fatigue that does not seem to improve with rest, and is wholly disproportionate to recent activity. CRF may limit the ability to perform daily activities including personal, social and occupational roles, and can severely impact our quality of life. Unlike typical fatigue, CRF is better described as multifactorial, potentially caused by anemia, hormonal shifts, systemic inflammation and psychological conditions such as depression and anxiety (Yang et al. 2019). Peripheral neuropathy is another very common form of impairment, more so in patients receiving chemotherapy with taxanes, platinum compounds or vinca alkaloids. Chemotherapy-induced peripheral neuropathy (CIPN) can result in experienced numbness, tingling, pain and weakness in the limbs. These symptoms can limit our gait, balance and manual dexterity, increasing the risk of falls and reducing independence in daily activities. Lymphedema is a chronic condition that affects the body’s lymphatic system and is particularly prevalent in breast cancer survivors who have undergone axillary lymph node dissection or radiation therapy, as it pertains to the swelling caused by the lymphatic fluid building up. Some of the risk factors include discomfort, a feeling of heaviness, reduced range of motion and infection. Furthermore, the condition can lead to psychological consequences due to the changes in body image brought about by the chronic nature of lymphedema. Myalgias alongside certain chemotherapy treatments such as hormone therapy tend to be a worrisome factor. These symptoms may lead to post-surgery pain and movement restriction, stiffness and fibrosis induced by radiation therapy, and generalized soreness. Taking the case of suffering from breast cancer of a woman sensitive to hormones, the use of aromatase inhibitors results in a joint pain which makes the quality of living – as well as the quality of life and adherence to treatment – poor. Considering the depth and complexity of the aforementioned physical disabilities, organized rehabilitation strategies are extremely important. Physiotherapy is fundamental in aiding the recovery of the patient’s physical performance and the disability prevention, and overcoming further disabilities. Moreover, other professionals get together to cover the complex needs of patients, including physiotherapists, other occupational therapists, oncologists, and psychologists, forming multidisciplinary care teams (McNeely et al. 2016). Exercises designed to reverse muscle wasting, improve balance and coordination to minimize falls, maintain radiation-induced stiffness, and enhance energy and stamina in the cardiovascular system to alleviate fatigue are all parts of the plan. The integration of technology into cancer rehabilitation is intended to improve the effectiveness, ease of access and customization of physiotherapy. In recent years, the adoption of wearable technologies and artificial intelligence (AI) systems have greatly enhanced rehabilitation practices. The primary advantage of wearable technology is its ability to passively track a patient’s routine physical activity, as well as their physiological parameters (heart rate, gait, etc.), and compliance to prescribed exercise regimens. Smart watches, motion sensors and inertial measurement units are examples of devices which allow real-world data collection in real time, which clinicians can later access (Kheirkhahan et al. 2019). Along with real-time data, these technologies provide many other objective measurements to supplement or completely replace subjective self-reporting. This minimizes variability in assessments and helps clinicians make informed decisions regarding the progression or amendment of the therapy. Quantifiable metrics such as, but not limited to, step count, range of motion and joint angles can be measured and used to assess treatment efficacy. Additionally, AI platforms can improve personalization by examining patterns in large datasets related to recovery trajectories. These platforms are capable of customizing exercise prescriptions to suit specific patient profiles, preferences, activity and trend within the data. ML algorithms may dynamically adjust the level and type of exercises to be performed to optimize results while avoiding overexertion or injury (Abasi et al. 2025). Remote accessibility is another key benefit. Virtual physiotherapy sessions, tele-rehabilitation platforms and mobile health applications can eliminate geographical and logistical boundaries. This is especially useful for patients who live in rural or medically underserved regions, have limited mobility, or during times of immunosuppression when health risks make in-person visits dangerous. Wearable devices refer to sensors and electronics embedded in accessories such as smartwatches, chest straps and clothing. They measure parameters such as movement, heart rate, muscle activity and more. Wearable sensors are integral to modern health and fitness monitoring systems, each tailored to measure specific physiological or biomechanical parameters. Accelerometers are widely used to detect movement, step count and general activity levels, and are commonly embedded in smartwatches and fitness trackers. Gyroscopes, often integrated within inertial measurement units (IMUs), assess orientation and posture, enhancing motion tracking capabilities. Electromyography (EMG) sensors monitor muscle activity and are typically found in surface EMG wearables designed for athletic and rehabilitation purposes. Electrocardiography (ECG) and photoplethysmography (PPG) sensors measure heart rate and heart rate variability, with applications in smartwatches and chest strap devices for cardiovascular monitoring (Prieto-Avalos et al. 2022). Pressure sensors capture data on gait and balance and are implemented in devices such as smart insoles and pressure mats. Lastly, temperature sensors track body or skin temperature and are often embedded in patches or wristbands to monitor thermoregulation and detect fever or metabolic changes.
11
AI and Wearable Technology in Physiotherapy for Oncology Patients
11.1. Introduction
11.2. Background and motivation
11.2.1. Cancer rehabilitation needs
11.2.2. Role of technology in rehabilitation
11.3. Wearable technology in oncology physiotherapy
11.3.1. Types of wearable sensors
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